Two very different worlds, one based on humans and the other on technology, are becoming one blended, scalable solution we are calling Services-as-Software. In short, the line between services and software is blurring and eventually vanishing, and this progression has become more crucial than ever.
Sixty percent of enterprises are already looking to procure services as technology offerings
A recent HFS study of 1000 major global enterprises reveals what is happening with stark brutality: Six out of ten enterprise leaders plan to replace some or all of their professional services with some form of AI within the next 3-5 years.
Services will continue to reduce their reliance on labor as automation creates more efficiency and productivity
The reality is that most people-based services, once they become predictable and routine, eventually become automated. This increasing sophistication of AI tools is enhancing the whole service efficiency and personalization experience. Once implemented effectively, these Services-as-Software solutions become faster to manage, cheaper to maintain, and more scalable to cope with volumes of demand.
For example, fully automated passport gates at airports now allow for higher volumes of passengers to clear immigration much quicker than previously and for more airlines to land their planes at the airport. This leads to more profitability for the airport, more business for the airlines and people to enter the country more expediently. Similarly, self-checkouts at grocery and convenience stores are enabling many more customers to have their purchases processed simultaneously, securely, and faster, which creates the ability to handle volume spikes without layering on unnecessary staffing costs to cater to demand.
Software-driven services can also improve the customer and employee experience
Now the airport can redeploy its people to manage issues at the passport gate when needed, to help shepherd them into the right lines, and also to provide assistance to elderly or disabled people. The whole experience is improved. Similarly, the convenience store can redeploy its staff to help customers find the products they need, to ensure inventory is better managed, to help manage in-store promotions, and to ensure the store is kept clean and presentable. Again, the customer and employee experience should be vastly improved, and the automation of the rote work allows more focus on improving the speed and quality of the whole business proposition.
While fairly simplistic, these are current real-world examples of how software embedded in enabled machines can not only replace the dependence on people to meet outcomes, but also enable organizations to scale their services without adding linear cost. The only differences with the emerging Services-as-Software model are the improvements in botifying routine white-collar work that was previously too challenging to automate due to limited technologies such as RPA and the absence of our ability to mimic and predict human behavior with the increasing sophistication of GenAI and Agentic software.
Services and software are equally exposed to full automation and AI
Enter the world of IT and business process services, and similar trends are in play as routine IT maintenance, HR, procurement, accounting, and customer service work are becoming much easier to replicate in advancing GenAI and Agentic software, supported by public and private cloud capabilities to secure and scale transaction volumes.
You only need to observe the rapid decline of growth in the labor-intensive services sector and the determination of enterprise customers to renegotiate both their services and software contracts to understand this dynamic is now in full swing:
Organizations face mounting pressure to deliver results faster, at scale, and with limited resources—all while managing increasingly complex technology ecosystems. The convergence of services and software meets that demand by transforming traditional consulting and outsourcing into scalable, automated solutions.
The 2030 destination is Services-as-Software, where the focus is on service provision performed by AI, not people
With the application of software platforms, Agentic solutions, and, ultimately, autonomous services mimicked by software, we believe we are on a fast track to reach an autonomous, human-lite nirvana of scalable, profitable, and affordable services by 2030:
These five phases of services tell the complete story of the industry’s evolution from adding people to perform work to scaling these same people with the smart use of platforms, AI-driven Agentic tools, and ultimately fully autonomous technology-led services where work is effectively replicated at scale with embedded intelligence.
In short, we are getting more of the same work without having to spend more on that same work. Instead, we can invest that money in value-added areas that cannot be mimicked by AI. Enterprises must adapt quickly to this shift as Agentic AI can autonomously handle complex decision-making tasks. This will impact both workforce roles and the enterprise software landscape, reducing the need for repetitive, decision-heavy positions and consolidating software functions under AI-driven platforms.
How the lines between services and software are blurring
This new model allows businesses to access continuous insights, predictive analytics, and outcome-driven solutions that adapt in real-time. It’s not just about streamlining operations; it’s about fueling growth and resilience, accelerating companies ahead in a world where speed and adaptability are critical to success. Let’s explore how this is already happening at speed:
Services-as-Software (SaaS 2.0): Providers like Workday and ServiceNow are shifting from traditional consulting models to plug-and-play solutions that automate once-manual tasks. Workday’s People Analytics and ServiceNow’s ITSM are prime examples—what once required hours of consulting is now pre-packaged expertise delivering instant results.
SaaS as the New Backbone: SaaS is evolving from cloud-based software to a powerhouse of built-in value. Platforms like Salesforce’s Customer 360 bundle sales, service, and marketing insights into one, reducing the need for external CRM optimization by embedding industry-specific expertise and a single customer view across the lifecycle right within the software.
AI-Driven Productization: AI tools like IBM Watson and Microsoft Power Automate are replacing traditional consulting roles with automated intelligence. IBM Watson isn’t just a chatbot but a full-scale AI ecosystem that analyzes data and offers predictive insights, eliminating constant human intervention.
Platform Playgrounds: Ecosystems like AWS and Google Cloud go beyond tech infrastructure by integrating software and partner-driven solutions. AWS’s MLaaS, for instance, includes pre-built models from consulting firms like Deloitte, allowing its enterprise clients to tap into sophisticated AI solutions without custom builds. KPMG has invested significantly in the GenAI platform Rhino.ai to modernize legacy applications, while, and IBM has been developing out its watsonx platforms to replicate many routine business services in a one-to-many scalable delivery model.
Outcome Obsession: Companies like SAP and Infor focus on outcome-driven solutions, with SAP’s Business Network and Infor’s CloudSuite tracking tangible results across supply chains and inventory. What once required armies of consultants now fits into a single, outcome-focused software solution.
Data as a Weapon: Platforms like Palantir Foundry and Snowflake are redefining data-driven insights. Palantir Foundry continuously analyzes business data for actionable intelligence, while Snowflake’s Data Cloud empowers companies to uncover trends and act proactively without needing an in-house data team.
The Bottom-line: In this new service-as-software era, the distinction between service and software is practically erasing.
Businesses now access pre-built solutions, automated workflows, and data-powered insights, creating a seamless and scalable experience that puts the power of technology and expertise directly at their fingertips. Services firms will increasingly look to their software partners and investments to streamline and provide greater value to entrprise clients, as this GenAI ecosystem unfolds. This model doesn’t just support business goals—it accelerates them, transforming how companies achieve impact in a world where speed and adaptability are the ultimate competitive advantage.
The challenge we all face – whether we buy, sell, advise or analyze this merging of markets is changing how we articulate, commercialize and deliver outcomes. Services and software people come from different worlds and speak different languages, but now these need to come together in a way we can all understand and develop. We can’t simply buy shiny new S-a-S solutions and plug them in like we did with an ERP solution. This is where we need to define real business value, which can be delivered by AI technology and price according to that value and the desired outcomes we expect. There is a huge opportunity for service providers to guide their clients to a state where they are ready for S-a-S solutions. There is also the potential for services and software firms to merge together as this new market emerges – there are already multiple discussions and partnerships taking place that are readying for 2025 and beyond.
Welcome to the era of uncertain change, everyone… where uncertainty will breed opportunity!
Some technologies struggle to fulfill their potential and need to be laid to rest. However, there are technologies that simply came into the world before their time because if they are truly capable of delivering real business value, they will eventually find their time and place in the enterprise spotlight.
Blockchain was once the shiny object that captivated the tech world, a supposed cure-all that promised to revolutionize everything from finance to food safety. Then came the crash—overhyped promises fizzled, ICOs tanked, and blockchain’s media buzz was silenced except for the speculation around Bitcoin’s value. But guess what? Blockchain isn’t dead. The technology has evolved, grown tougher, and found its niche in critical industries. This is more than just a simple opinion – there’s data to support it. As our HFS Pulse data below reveals, the vast majority of enterprises still using blockchain today plan to increase their spending in the next two years – they wouldn’t do that without experiencing real value:
The blockchain hype machine kicked into overdrive around 2017, with headlines screaming about disruption and revolution across industries. Companies scrambled to plaster “blockchain” on every proposal, hoping to ride the wave of optimism. But much of that early enthusiasm was built on shaky foundations. As we pointed out in our infamous Blockchain Bullshit Buster (See our 2018 piece “Is blockchain a giant digital joke?”). Too many businesses leapt in with little understanding of the technology, banking on the promise without considering its practical use cases.
The inevitable happened: projects failed, the ICO bubble burst, and the market came crashing down. The blockchain-is-dead narrative took hold – using blockchain shifted from a badge of honor to one of shame – but it was an oversimplification. The hype died—but the technology didn’t. What came next was an evolution: businesses became smarter about where and how they deployed blockchain, shifting from broad, unrealistic ambitions to specific, high-value applications – all behind closed doors.
The symbiotic relationship between AI and blockchain can solve one of our biggest challenges: trust deficit
Now we’re almost two years into the GenAI revolution, one of the biggest benefits is the renewal of permission to consider technologies such as blockchain, which lost their way because of trust issues where enterprises simply weren’t prepared to open up their data to new innovative possibilities. Executives were more in fear of getting fired for experimenting with tech than they were in fear of being perceived as rejectors of innovation. AI is changing all of that in many ambitious organizations where C-Suites are challenging their colleagues to embrace a change culture and drive new AI innovation possibilities.
The intersection of AI and blockchain holds incredible potential, particularly in addressing one of society’s biggest challenges: trust. AI’s capabilities to analyze large amounts of blockchain data, paired with blockchain’s decentralized and transparent nature, could significantly reduce the trust deficit between consumers and corporations, as well as citizens and governments. Imagine a world where technology itself fosters greater confidence in systems that have long struggled with credibility issues. However, before we can leverage these advancements to build trust externally, we must first trust the technology itself—ensuring that it’s reliable, secure, and ethical. This is where the true power of this intersection lies:
Blockchain Thrives where Trust, Traceability, and Transparency are non-negotiable
Blockchain has matured, and those in the know recognize that it’s making strategic inroads in industries where trust, transparency, and traceability are non-negotiable. Here are our top 10 favorite real-world examples of how enterprises are deploying blockchain today:
Walmart & IBM (Supply Chain Transparency): Blockchain’s ability to create transparent, tamper-proof records is revolutionizing supply chains. Walmart has partnered with IBM on its Food Trust blockchain, which tracks the journey of food products from farm to table. The result? In cases of contamination, Walmart can trace the origins of food products like leafy greens in 2.2 seconds, a process that used to take days. This not only enhances food safety but also reduces the impact of recalls, lowering operational costs for Walmart.
JPMorgan & Liink (Banking & Finance): In the financial sector, JPMorgan’s Liink platform, part of its Onyx blockchain division, connects more than 400 financial institutions to streamline cross-border payments. Liink enables banks to securely exchange payment-related data, reducing delays and improving transparency. This is critical in addressing the inefficiencies in $30 trillion worth of annual cross-border payments.
Mastercard has launched its Provenance Solution using blockchain to trace the origins of goods along supply chains, ensuring authenticity. Through this platform, Mastercard tracks the source of goods like luxury items and pharmaceuticals, allowing retailers and consumers to verify the legitimacy of the products.
Ripple (Cross-Border Payments): Ripple’s blockchain technology is used to handle cross-border payments efficiently, challenging the SWIFT network. Banks like Santander and American Express have partnered with Ripple to process payments faster and more cost-effectively. RippleNet, Ripple’s global payment network, allows financial institutions to process international payments in seconds instead of days, reducing operational costs and improving liquidity.
Pfizer & MediLedger (Pharmaceutical Supply Chain): In healthcare, Pfizer and other pharmaceutical giants are using the MediLedger blockchain platform to improve the transparency and security of the pharmaceutical supply chain. With counterfeit drugs representing a major challenge globally, blockchain ensures the authenticity of drugs from manufacturing to delivery. This guarantees that medicines prescribed to patients are genuine, thereby improving safety and compliance.
Procter & Gamble & Plastic Bank (Sustainability): Procter & Gamble (P&G) is partnering with Plastic Bank, a blockchain-powered social enterprise, to encourage recycling in coastal communities. Blockchain ensures transparency in the collection and recycling of plastic waste by giving communities access to a digital ledger that tracks plastic collection and recycling rates. Collectors are paid in a digital currency through the blockchain, fostering a circular economy while reducing ocean-bound plastic waste.
Nestlé & OpenSC (Food Safety): Nestlé uses blockchain to track the entire journey of its sustainably sourced coffee and milk. The company partnered with OpenSC, a blockchain platform, to give consumers visibility into how their food is produced and shipped. Nestlé’s blockchain initiative enables customers to verify the source and sustainability of their products by scanning QR codes on packaging, providing unparalleled transparency in the food industry.
Siemens (Energy): Siemens is leveraging blockchain technology for energy trading in microgrids. Siemens is piloting a blockchain-based energy trading system that allows decentralized energy producers (such as homeowners with solar panels) to sell excess energy directly to their neighbors. Blockchain simplifies transactions, ensuring transparency and reducing reliance on traditional utilities.
De Beers (Diamond Tracking): De Beers, the world’s largest diamond producer, uses blockchain to track diamonds from the mine to the consumer. Through its Tracr platform, De Beers guarantees the authenticity and conflict-free status of its diamonds, providing end-to-end visibility in the diamond supply chain. This helps reduce the prevalence of “blood diamonds” and ensures ethical sourcing.
Unilever (Sustainability and Supply Chains): Unilever has been piloting a blockchain platform to track the sustainability of its palm oil supply chain. The platform ensures that the palm oil it sources comes from sustainable farms and adheres to environmental and ethical standards. Blockchain helps verify that suppliers are compliant with Unilever’s sustainability goals, reducing deforestation and improving transparency for consumers.
Even governments are getting in on the action, exploring blockchain for applications like digital identities, land registries, and voting systems. These are high-stakes use cases that can’t afford failure, and blockchain’s decentralized and transparent nature is exactly what’s needed. The backing of public institutions is further proof that blockchain’s longevity isn’t in question—it’s inevitable.
The hype needed to die so that blockchain could get real.
It’s easy to mistake the cooling hype for blockchain’s failure, but this couldn’t be further from the truth. The technology is now living up to its potential—not as a universal fix, but as a tool with targeted, high-impact applications with trust, traceability, and transparency at the core.
Blockchain’s early downfall came from misaligned expectations—companies that treated blockchain as a solution in search of a problem quickly saw their projects fall apart. But today, we see real deployments that address industry-specific pain points. The so-called “blockchain winter” didn’t kill the tech, it forged it.
One reason blockchain was written off too soon was because of its early scalability and privacy issues. Bitcoin and Ethereum, the poster children of the blockchain movement, struggled to handle high transaction volumes and a perception that a technology built on transparency couldn’t offer any level of privacy. Critics were quick to pounce, labeling the technology impractical for large-scale use. But those issues are fading. Layer 2 solutions (think Ethereum rollups) and cross-chain interoperability protocols have unlocked blockchain’s potential for larger-scale applications and enhanced privacy – we highlighted these innovations here. And it’s happening right under the radar—while the media stopped talking, the developers are still building.
Improved interoperability between different blockchain networks means enterprises no longer need to be shackled to one platform. We’ve seen partnerships between tech giants, including Microsoft and Amazon, offering Blockchain-as-a-Service (BaaS), making it easier for companies to experiment and deploy blockchain in a modular, scalable way.
Failure is a Part of Blockchain’s Evolution
As with any new technology, blockchain has had its share of failures. However, these failures don’t signify the end of blockchain’s potential—they are part of its evolution. High-profile projects may have struggled, but these are valuable lessons that help drive the technology forward. It’s important to understand that blockchain isn’t a magic bullet—it needs to be deployed strategically with realistic expectations and a clear understanding of the problems it solves.
Some high-profile blockchain initiatives, such as TradeLens, have not lived up to their initial expectations – and we covered this specific example in January 2023. In late 2022, Maersk and IBM announced the decision to shut down TradeLens, citing the platform’s failure to achieve the necessary commercial viability and collaboration needed to scale across the industry. The demise of projects like TradeLens sheds light on some critical factors:
Adoption and Network Effects: One of the biggest challenges for blockchain platforms like TradeLens is achieving widespread industry adoption. While TradeLens signed up some major shipping companies and port authorities, it didn’t bring on enough players to create the necessary network effect. Blockchain, especially in supply chain and logistics, thrives on collaboration between multiple stakeholders. Without critical mass, the benefits of transparency and efficiency diminish, making it harder for the project to sustain itself.
Legacy Systems and Industry Resistance: Blockchain often has to compete with deeply entrenched legacy systems. In the case of TradeLens, many logistics companies and customs authorities were hesitant to abandon their existing systems, which were highly customized for their needs, in favor of a new technology that required significant changes in infrastructure and operations. The same applies to other industries where blockchain has to integrate with or replace complex legacy systems.
Cost and Complexity: Implementing blockchain solutions can be costly and complex. TradeLens required significant resources for integration and maintenance. In industries with thin margins, like shipping, companies may be reluctant to make these upfront investments, especially if the long-term value proposition is uncertain. Blockchain platforms also demand interoperability between various players’ technologies, which adds to the implementation burden.
Ecosystem and Trust: Blockchain projects, especially those like TradeLens that rely on multi-stakeholder participation, can fail when there isn’t enough trust between parties. TradeLens needed buy-in from competitors, governments, and intermediaries, but in many cases, these parties were reluctant to cooperate, citing concerns over data sharing and competitive advantage.
Failures provide insights on what doesn’t work, but they also highlight the areas where blockchain has the potential to thrive. Businesses are learning to focus on practical, industry-specific applications that address real problems, rather than using blockchain just because it’s the trendy thing to do.
Bottomline. Blockchain winter has forged a stronger, more focused technology that is now solving critical challenges across multiple sectors.
The early frenzy around blockchain may have passed, but that’s not a death knell—it’s a sign of the technology’s maturity. Blockchain is now in its proving ground phase, with tangible, transformative use cases emerging across industries like finance, supply chains, and healthcare. The death of hype isn’t the death of blockchain; it’s the beginning of a more grounded, valuable era.
Blockchain isn’t about spectacle. It’s about solving real business challenges, and it’s already doing just that. So, while the headlines may have moved on, blockchain hasn’t—it’s here, it’s scaling, and it’s delivering results.
Why do enterprises buy services? Because they need “work” performed that can be managed more effectively by people outside of their company. However, by 2030, we will be engaging with “services” primarily through technology, minimizing human intervention and maximizing efficiency. In fact, services will barely even be services anymore…
As the world absorbs the incredible impact of technology and the internet on their businesses, the need for competent third parties to integrate, maintain, and innovate technology has consistently resulted in more and more spend each year. Talk to any CIO or CFO today, and they will bemoan the perpetual annual cycle of more and more money being spent on the cloud, on expensive software licenses, and all the people needed to keep this never-ending thirst for technology slaked.
We must break this death spiral of piling up our legacy debts if we want to stay in business
The problem today is enterprises cannot keep funding this incessant linear growth into perpetuity. They’ve been piling on considerable debt, which is becoming unsustainable as their people become administrators of legacy systems, broken processes, and useless data. Their cultures have become ones of sustaining old business practices and creaking business models, fuelled by a desperate fear of change and having to learn new and different ways of doing things. At HFS, we estimate the technology debt being sustained across the global 2000 to be close to $2 trillion.
And our beloved services industry has profited from this enterprise lethargy and perpetual spending for decades. The practice of piling on kids schooled from Indian universities to document these legacy practices so they can keep delivering them on multiyear contracts, where they can consistently find ways to keep layering on even more people and load yet more cost back onto their jaded enterprise clients, has become an art form. However, this gravy train of constant growth has run its course, with most services firms content with revenue growth that is barely even keeping pace with inflation. The reality is most of the services industry is not ready to retire, and we urgently need to innovate service provision to stay relevant in this game.
It’s all about scaling businesses with technology that enhances our existing people
The good news is the need to scale services without scaling people is upon us, and with it comes a massive opportunity if we can drive the hard changes necessary to repay these legacy debts. With the application of software platforms, agentic solutions and, ultimately, autonomous services mimicked by software, we believe we are on a fast track to reach an autonomous, human-lite nirvana of scalable, profitable and affordable services by 2030:
These five phases of services tell the complete story of the industry’s evolution from adding people to perform work to scaling these same people with the smart use of platforms, AI-driven agentic tools, and ultimately fully autonomous technology-led services where work is effectively replicated at scale with embedded intelligence.
The 2030 destination is Service-as-a-Software, where the focus is on service provision, which doesn’t really involve services anymore
In short, we are getting more of the same work without having to spend more on that same work. Instead, we can invest that money in value-added areas that cannot be mimicked by AI. Enterprises must adapt quickly to this shift as agentic AI can autonomously handle complex decision-making tasks. This will impact both workforce roles and the enterprise software landscape, reducing the need for repetitive, decision-heavy positions and consolidating software functions under AI-driven platforms.
As this landscape continues to evolve with more major players launching agentic solutions, ambitious startups such as Mindcorp.ai, rhino.ai, and Lyzr will differentiate by offering unique capabilities, ensuring cross-platform compatibility, and demonstrating cost-saving benefits to appeal to enterprise clients. These emerging solutions are forcing the breakaway from legacy technologies and the reinvention of business models to take full advantage.
Net-net, the impact on services, as demonstrated above, is an increasing reliance on machines to fulfill the complex tasks previously delivered by people. We are eventually heading towards Service-as-a-Software, where the focus will be on service provision, which doesn’t really involve services anymore. Instead, we will be delivering “services” primarily through technology, minimizing human intervention and maximizing efficiency.
Writing off legacy means partnering for change
Ambitious enterprises and their service partners are both striving to be effective in the emerging world of these AI-driven business models and operations. This means this transition only works when there are two parties ready to tango and change together. To this end, service providers must become partners of change for their clients to help them understand the sheer noise of technology change going on around them. Clients need internal alignment to ensure that it’s time to make the move.
The shift from labor to technology doesn’t take away the need for people; it actually necessitates experts who can shepherd their clients along to help them change. They must provide continuous education on how to manage organizations’ fast-moving technology ecosystems and work with them to create business roadmaps based on emerging tech to make them slicker, smarter, more efficient, and less bloated.
Enterprises are buying service solutions that improve performance, accelerate time to market, reduce costs, and create new content and data. We must address our debt across our entire data infrastructure, our processes, our skills and our tech, which our firm has likely collected over the last 30+ years:
1. Fix your data debts: You must align your data needs to deliver on your AI-centric business strategy. This is where you clarify your vision and purpose. Do you know what your customers’ needs are? Is your supply chain effective in sensing and responding to these needs? Can your cash flow support immediate critical investments? Do you have a handle on your staff attrition?
2. Fix your process-debts: Recreate new processes process to determine what should be added, eliminated, or simplified across your workflows to support your slicker AI-led operating model.
3. Fix your skills debts: Develop new skill sets that can support the transition to embracing emerging technology and AI-driven business models.
4. Fix your technology debts: IT spending just keeps increasing and only keeps swelling with each new platform and coding change. Stop buying tech for the sake of tech—this has been the failure of so many previous investments, such as the two-thirds of enterprises left struggling with their cloud migration journeys signed during the pandemic.
The Bottom-line: Enterprises can only repay their debts by adopting a technology-first approach
Enterprise leadership has always been – and still is – obsessed with cost reduction. This is what they understand more than anything, and they view innovations such as GenAI as another lever to justify investments based on yet more cost take-out. The best approach is to reduce overall delivery costs by investing in change and technology that can scale services. This is offset by the increased value and reduced labor costs driven through effective investments in change, processes, data, and technology. Clients MUST sign up for process reinvention and data transformation as part of it. Clients need to TRUST their partners to get them there. Providers need the TALENT to work with their customers, or the whole thing simply erodes to the bottom.
What enterprises desperately need are partners to work with them who share similar desires to learn new methods, unlearn old habits, and to teach them to exploit new technologies and new data methodologies and work with them to attack new markets with these capabilities.
The big question now is whether enterprises and their services partners have the appetite to fix their skills, processes, data, and technical debt? Can they really learn new ways of operating, change their cultures, and embrace emerging technologies? Everyone needs to dig deep and decide whether they want to be a footnote or the future.
We are hurtling towards a US presidential election in which only a small proportion of people are fully aware of the consequences, whether it be the economy, immigration, healthcare, education, the climate emergency, and so on. While Kamala Harris has been specific regarding her policies, we need to examine Project 2025 to understand where policies are likely to be set under the Republican administration.
What concerns me a great deal is the proposed removal of the Patient Protection and Affordable Care Act (ACA)—previously called Obamacare—by the Heritage Foundation that we fully anticipate this Republican administration to execute, especially after President Trump’s determined -(but failed) attempts to repeal the ACA during his previous term. Essentially, when we remove the ACA, we will reverse history back to before 2010, when citizens could be refused insurance coverage for a pre-existing/chronic condition, which today impacts six out of ten citizens, according to the CDC. This will have a huge impact on both citizens and their employers as so many people struggle to access the urgent care they need.
HFS’ lead healthcare analyst, Rohan Kulkarni, has endured the US healthcare system for 16 years as a CIO, strategist, consultant, market maker, and now an analyst who has delved deep into the consequences of Project 2025 on US healthcare to understand what to expect. Over to you, Rohan…
The US presidential elections could reshape healthcare across the quad-aim of care
Elections always have consequences; this one in 2024 will impact life and death, particularly for certain population demographics. The choice in the 2024 election is between improving the Patient Protection and Affordable Care Act (ACA), the law of the land, or significantly diluting it with Project 2025, the conservative agenda published by the Heritage Foundation. The exhibit below reflects Project 2025’s healthcare goals and its impacts on the quadruple aim of care (reducing the cost of care, enhancing the experience of care, improving health outcomes, and addressing health equities), which will reverse the progress made over the last decade relative to the cost of care ($0 premium Medicare Advantage, exchange plans), health equity, access to care (lowest uninsured levels ever), and even health outcomes in some limited contexts.
The healthcare-related goals of Project 2025 are intrinsically regressive
Project 2025 lists five goals for the US Department of Health and Human Services (HHS), as shown in Exhibit 2, that form the foundation of a new healthcare paradigm. These goals are a mix of non-healthcare aspirations, such as marriage, and non-scientific assertions like “abortion” and “euthanasia” are not healthcare. The goals are framed to transform US healthcare without the need for Congressional action, rather through the executive actions of the Secretary of HHS.
The first goal aims to ban abortion federally and ignores transgender realities, diminishing equity in healthcare. In meeting the first goal, project 2025 will drive poor health outcomes by ignoring underserved communities that often need the most help. In particular, a federal abortion ban that leaks into other women’s health affairs will curtail access to care as obstetrics and gynecologists quit the field, as we see in many states that have banned abortion.
The second goal is to empower patient choices and provider autonomy, which are already part of the healthcare system. The ACA marketplaces allow consumers to shop and buy health insurance based on their needs, from bronze plans with high deductibles to silver with moderate deductibles to gold and platinum with low deductibles, plans for everyone’s affordability and health needs. ACA provides government subsidies to buy the plans based on income levels. Project 2025 seeks a paradigm that existed prior to ACA, where health insurers could decline to cover consumers and use pre-existing to deny care. As part of the ACA plan selection, consumers, based on their location, can choose from a significant number of providers across specializations. A central tenet of good care delivery is the patient-provider interaction without outside interference, which is generally true in the current context.
The third goal warrants HHS to minimize and possibly ignore same-sex marriages and the needs of LGBTQ+ by emphasizing traditional marriages between a man and woman. While those go against existing laws that the Supreme Court has upheld, there is no empirical evidence to show same-sex marriages yield in families that are any less productive, happy, or have a negative bearing on our society. Project 2025 not only designs a path to return to times of expensive healthcare with poorer health outcomes but attempts to transform society by biasing its plans towards certain demographics.
Goal number four seeks to abandon public health strategies to mitigate pandemics, such as forced lockdowns, isolations, and vaccine mandates. Project 2025 asserts that these techniques with COVID-19 led to distrust in the health agencies and more unnecessary deaths. However, there is significant evidence that those techniques worked, here in the US and overseas, to prevent the spread of disease and reduce deaths. A state-by-state review of COVID-19 deaths shows an increase in per capita deaths in states that refused to follow locked-down and isolation protocols, delayed the delivery of vaccines, and mismanaged communications.
The last published goal intends to reduce the influence of pharmaceutical and healthcare enterprises over the functioning of agencies. It seeks to eliminate the revolving door between government and the private sector. While that is laudable, Project 2025 does not address where expertise will come from to help progress the government’s understanding of science to inform policy. It further goes on to indicate the need for a new set of metrics to determine the extent to which HHS policies and programs achieve desired health and welfare outcomes, something that is already in place with significant checks and balances.
The Bottom Line: Project 2025 seeks to kill the ACA and remake US healthcare through HHS and without legislative action.
Political noise leading up to any election can make the future fuzzier than it is. However, Project 2025 provides a blueprint of how healthcare will be remodeled. Project 2025 proposals suggest a regressive impact on the quadruple aim of care, setting America back to a healthcare paradigm before the enactment of the ACA in 2010 when selective coverage or denial of care for pre-existing conditions was the standard. It is essential that employers remain true to the health and care needs of their employees, adjusting their strategies under a drastically different regulatory framework.
I’m delighted to announce that the analyst who made sustainably great… is back to MAKE SUSTAINABILITY GREAT AGAIN! Yes, folks, Josh Matthews has returned to the HFS analyst family! And in time to meet many of you at the HFS AI Symposium at Cambridge University.
Josh, it’s great to have you rejoin the HFS family. It seems like you’ve had an eventful time in the outside world the past couple of years. What were the highlights? What did you learn about the world?
I’ve spent 2 years zigzagging through the different parts of the climate and sustainability emergency. I’ve come through with a clearer understanding of the global context and how the systems that need changing operate. I’ve seen the insides of large services firms, multiple climate and sustainability startups, experienced the processes and emotions of COP28, and gotten involved in climate finance and sustainable city initiatives. Having also stood for Parliament in the UK’s general election, I will continue to be involved in politics – especially tying in all things sustainability from environmental and social perspectives – linking the global context to people’s lives and local areas. I don’t think I’d be able to stand by and not have a political part of my life given the systemic change sustainability needs across policy, consumer behavior, and business. It’s exciting that HFS has always been able to influence at both a systems level and the detailed strategic, technology, and process levels that real progress needs.
I remember well the great work you did building up our sustainability coverage and the great impact we were making influencing enterprise leaders. With all the recent changes in the global economy and the sorry state of global politics, will you change your messaging/research to the world?
I’m going to tackle two ends of a sustainability spectrum which seems to be diverging more and more. On one end is the critical mass: The coming together of people and organizations to prove sustainability works in all its environmental, social, and economic ways – pulling along policymaking, consumer behavior, and business along into alignment with the trajectories of the Paris Agreement and UN Sustainable Development Goals. It’s why I set up Critical Mass for Sustainability and look forward to using it as a convening and advocacy platform alongside HFS’s research and consulting. On the other end of the spectrum, is the need to embed sustainability throughout an organization’s plans and processes. Embedding sustainability is all the more important when moving first is a tough sell to clients, employees, or the public.
The sustainability spheres of influence are still vast for companies, whatever part of their value chain they find themselves in. That is especially true for the biggest, most influential enterprises. It is also true for the biggest consulting, technology, IT, engineering, and business services firms. Their potential impact is as large as it was when we launched our Sustainability Services market analysis two years ago. Companies in every industry need to move so quickly to address sustainability. Services firms will need to be there alongside them, having understood their sectors, business models, and operations.
If services firms push their clients and partners to be a part of a critical mass then they can be the architects of the positive tipping points sustainability needs. If they can embed sustainability into their services, then they can have impact regardless of whether clients demand sustainability or not.
And what do you intend to write about in the coming months? Where do you feel enterprise leaders need attention? How do you plan to draw their attention away from other issues?
I’ll be working across the whole HFS team to keep embedding sustainability in our own research, advisory, and convening work. Whether that’s industry, technology, or business functions. I’ll continue my work of breaking down the global sustainability context and helping align people, teams, and companies. When a vast geopolitical mess confronts us all, being clear on where your spheres of influence are as a person or business – clear on what is materially impactful, not only what sounds right – is all the most vital.
I did admire how sustainability was becoming big business for leading professional services and tech firms, but that seems to be slowing. Is that really the case?
We need to show that the supposed ESG backlash or “greenlash” is nothing more than a “greenhush” at most. That doesn’t mean sustainability isn’t facing challenges. Far from it. But the arc of progress is still bending towards the Paris Agreement, net zero, and the 17 UN Goals. We’re nowhere near on track. But we’re not slowing. In fact we’re still accelerating despite all the noise and lobbying for it to be otherwise. Just to take a few examples from the past week or so… I plan on adding to this argument with HFS’s research power behind me.
A study of over 2100 C-level execs by Deloitte found 85% of them increased their sustainability investment over the past year expecting direct benefits. Published at the same time, a Bain study looked at B2B and B2C customer sustainability attitudes. Demand is high. But separate analyses of multiple reports suggest CEOs are deprioritizing sustainability when considering the multifaceted geopolitical chaos of the last few years. But de-prioritization is a loaded word – and doesn’t (or shouldn’t) always translate into spending (often priorities in surveys like this reflect what’s top of mind). The long-term implications are amplified when limiting strategic, operational, and financial resources to sustainability goals. Like trust, lost sustainability momentum and progress can take a long time to build back.
The Deloitte study actively shows there is no material de-prioritization but an acceleration of spending and action. Also consider that the “public facing” de-prioritization in rhetoric from some CEOs and firms confronted with a volatile and unpredictable US election… might not be translating entirely into the work of other execs and operational leaders as they press on. (Also also, IRA money is unlikely to go anywhere given its allocation in Red states and their broader economic potential for sustainable energy and infrastructure).
Sadly many businesses and politicians worldwide have found it far too easy to accept the idea of an ESG backlash – because sustainability is hard. Sustainability can work on all environmental, social, and economic fronts. And those who prove that will be a part of the critical mass that creates positive tipping points and pulls along policy, consumers, and businesses. But that doesn’t mean sustainability is easy or the immediate business case is always obvious.
We need to think transition plans.
We know where we’re heading – the UN Sustainable Development Goals (SDGs) make for terrific roadmap endpoints. And even if all the data isn’t available, there are enough examples of success out there to work out what’s material to your business and to sustainability – to know your starting point and move forwards on the trajectories of the SDGs and Paris Agreement. The near future timeline for sustainability is uncertain, but the long-term timeline is not. It cannot be.
And finally, Josh, the biggest negative impact of AI is the sheer amount of energy required to fuel these scaling LLMs and power these Nvidia chips. Where do you see this all going? Is AI really worth it, or are there things we can do to minimize the negative impact?
Judging by the progress of Google, Amazon, Microsoft, et al. on procuring and building immense amounts of renewable electricity generation – the emissions footprint of technology use doesn’t worry me as much as other factors. Solar and wind are proven technologies and are cost effective at vast scale – we just need to build more. The material and industrial waste footprints are far from solved however. Industrial waste is roughly 95% of global waste – with 5% coming from consumers. Even in the UK where services dominate, consumer waste is maybe 10-15% at most. How we store all the solar and wind energy required for not only digital technologies but a more electrified future is also an outstanding challenge. Battery technology is improving but is far from where we need. Grids need upgrading – both physically AND digitally – which is where AI and other digital twin, IOT, and analytics technologies can find a powerful role.
Social impacts of AI and the whole sustainability transition will require careful planning.
Sustainability goes well beyond decarbonization and net zero to all environmental challenges including waste – industrial especially – water, biodiversity, and more. It also goes deeply into our societies. Social sustainability cannot just be corporate social responsibility (CSR) projects but must include a range of measures from a duty of care to your own employees’ wellbeing, to ensuring a just energy transition that works for the least advantaged most of all. Economically we must collectively work out where the upfront capital for sustainability comes from. In the long run everyone will benefit from a transition to the UN Goals – but the upfront costs must be derisked and be shared by those who can afford them. There’s a fantastic IEA report which delves into this from an energy transition angle.
HFS Research has been at the forefront of emerging technology for well over a decade.
From the rise of process automation to all things digital transformation to sustainability and now Generative AI. Cutting through hype and pointless press releases. Focusing on outcomes. Focusing on case studies. On what works. On what could work.
Sustainability needs that approach more than ever. Systemic change. And embedding sustainability to pull along those who haven’t yet found their own case for change.
I wanted to share publicly that I am backing Kamala Harris for President. While she has been relatively new to the “big debate”, I have been persuaded by the following:
Support for small businesses and entrepreneurs. The future of job creation and innovation isn’t going to come from most monolithic large enterprises, which are slaves to quarterly earnings and obsessed with profit – so many are focused on their shareholders a lot more than their people. It’s going to come from small businesses that want to grow, which can easily exploit new technologies to scale and can train people to be at the heart of their business models. Many small businesses also provide many more opportunities for ethnic minorities, where so many large enterprises have failed. She will expand the startup expense tax deduction for new businesses from $5,000 to $50,000 and ensure more federal contracts are distributed to smaller firms and not the usual greedy enterprises on the gravy train.
While not perfect, the country is still in a great place economically. Let’s not risk that. We can argue all we like, but the fundamentals of inflation (now at 2%) are FAR lower than all the G7 countries, GDP growth is the highest in the G7 at 2.8%, median household income is growing at 4% (including inflation), while unemployment has been consistently at record lows while the stock markets have been hitting record highs.
Tax cuts and benefits must grow the economy and the middle-class, not just make the rich even richer. She is proposing restoring two tax cuts designed to help middle-class and working Americans: the Child Tax Credit and the Earned Income Tax Credit. They will also expand the Child Tax Credit to provide a $6,000 tax cut to families with newborn children. She has promised first-time homebuyers up to $25,000 to help with their down payments, which is a huge issue for GenZs desperate to get on the housing ladder. Noone earning less than $400K will be negatively impacted. As a business owner myself, I am fine paying a few extra dollars a year to support this country. I don’t know why these obscenely rich people need even more money to increase our national debt and lay on yet more burdens for our kids to pay off when we are retired happily on our boats and golf courses.
The USA desperately needs a woman president. America would sorely benefit from a smart, likeable woman to lead this country. There are too many gender diversity issues to even attempt to broach here, but having a woman leader would do so much to balance them in this country. It is pretty unthinkable that in 2024, the world’s superpower and most powerful economy has never had a female at the helm. This has to change.
The Bottom Line: Kamala Harris may not be the perfect answer, but she’s offering us opportunity and hope to fix a divided country
There are choppy waters ahead for the US, with a recession surely coming eventually, some awful military conflicts we need to help resolve, and some real divisive (and often unnecessary) issues threatening to tear this country apart. There also needs to be a deeper focus on healthcare and education in this country, and I am not yet convinced anyone has addressed this effectively.
However, I believe the US is still the land of opportunity. It was the country where I founded my first business in 2010, which has grown and prospered over the years. I have benefitted from great American talent and from great people from other countries over the last few years, and I still love doing business in a great country like this, which continues to have a strong entrepreneurial spirit and confidence in the future. I am backing Kamala because, in my view, she is our best bet to take us forward.
These are my personal views and do not represent those of HFS Research.
Being a Brit transplanted in the US, it is bizarre to me that the state of healthcare is not an election issue. In the UK, it’s the constant political hot potato – never enough funding, never enough nurses, doctors on strike, massive waiting lists for patients, etc. However, from my own personal experience, the waitlists are just as frustrating in the States, the IT systems are woefully integrated (and some actually worse than the UK’s NHS), the patient experience is very “transactional,” reactive, and rarely joined up, despite $5 trillion annually propping up this mammoth house of cards.
Fortunately, at HFS, we have a deep focus on healthcare and life sciences, which has taught me personally a lot about the core issues, so I asked our fearless healthcare lead analyst, Rohan Kulkarni, to name six big things we can address to fix these problems while American voters obsess about anything but their healthcare…
All attributes of the quadruple aim of care continue to head in the wrong direction
Given the strong financial incentives to perpetuate a system that operates without responsibility or accountability, nothing can be done to fix this sick care paradigm. At HFS Research, we measure the performance of US healthcare across the quadruple aim of care (see Exhibit below) – to reduce the cost of care, enhance the experience of care, improve health outcomes, and address health equities. Despite strong evidence of all elements of the quadruple aim of care failing its health consumers, there are no meaningful catalysts to trigger a change in direction:
However, there are 6 things that are still possible that may give us some relief…
1. Eat healthy and get off the couch
There is significant clinical evidence to suggest that those who are mindful of what they eat and maintain an active lifestyle tend to remain healthy compared to those who don’t. DNA certainly plays a part, but it is likely that a diet of saturated fats and high cholesterol combined with a sedentary lifestyle is not consistent with disease-free, high quality of life, and long life spans. It is, therefore, incumbent upon each of us to practice a healthy lifestyle (nutrition, activity, hygiene) if we want to remain relatively disease-free and postpone those healthcare visits.
2. Employers fire your health insurers
Despite all the fuss about AI, employees will likely remain an employer’s ultimate asset for the foreseeable future. It is, therefore, an economic imperative for employers to keep their employees healthy (sick employee = cost, healthy employee = revenues). To support a healthy employee population, employers must really explore underwriting the medical risk of their employees, especially those that are profitable, in a services business, and have limited liabilities. Those who are already self-insured must consider creating direct-to-provider constructs with a reasonable capitated fee that eliminates all those foolish administrative burdens like prior authorization and claims processing while getting a better quality of care at a lower price.
3. Consumers embrace subscription-based primary care
President Obama said in the throes of the Affordable Care Act fights of 2013 that healthcare would be cheaper than your monthly cell phone bill. He was not kidding. Subscription for digital health-enabled primary care is as low as $9.00 per month if you are an Amazon Prime member of OneMedical. Other providers charge between $50 and $200. Some even include a formulary with up to 200 most commonly prescribed medications. This is a catalyst for us to re-embrace primary care without the hassles of prior authorization and coverage constraints to manage our health proactively.
4. Forget CVS and Walgreens for Rx
Alternatives like Mark Cuban Cost Plus and Amazon pharmacy are making prescriptions significantly less expensive and easier to access, especially if they are generics. Each of these has a different approach, yet they are significantly less expensive than chain pharmacies, deliver to our homes, provide transparent pricing, and are becoming the go-to for generics. Employers and consumers must begin to include such alternatives in their prescription filling process to reduce their healthcare costs and stress.
5. Medical IoT and wearables will save us from us
The sick care paradigm that envelopes us is one driven by a demand-based intervention construct. It is where we, the individuals, decide how we feel and when to seek help. Given the proliferation of medical IoT, wearables, and the inclusion of AI to support diagnostics, we are at an inflection point to reset the care delivery paradigm. Consider leveraging all these technologies to enable a need-based intervention. Let the devices and data inform the clinicians when and for what to intervene. Employers and consumers can drive this shift as part of their direct-to-provider contracts to allow for continuous monitoring and need-based interventions that arguably save significant costs while improving health outcomes by intervening as needed and accurately.
6. Make healthcare equitable to all US citizens
Healthcare protocols are biased towards the majority demographics (white, urban, educated, and wealthy), leaving minorities and the underprivileged underserved and uncared for. Private-public partnerships must address these communities, given they are critical workforce levers if cared for. Consequently, community-based care constructs that incorporate social determinants attract community-specific resources to be the first line of triage that addresses trust gaps and addresses diseases that communities are pre-disposed to, e.g., Pacific Islanders are pre-disposed to obesity, as are African Americans to diabetes. Community and underserved focus is key to democratizing care to help improve local economies, address health equities, and improve health outcomes.
The Bottom Line: We are SOL in this sick care paradigm, but consumers and employers are best positioned to make incremental changes on their own that can be material.
The reality is that we can not keep doing the same things and expect different results. We must change what we do, leverage technologies, and be bold enough to experiment outside the legacy sick care paradigm. Short of that, our choice is to sit on the curb and whine about how our healthcare system sucks!
Global Capability Centers (GCCs) have emerged as the trailblazers of the Indian IT landscape, displaying extraordinary double-digit growth and transformation and carving out a distinct and powerful niche. While tech and BPO service providers have grappled with flagging enterprise demand and other market pressures, GCCs have thrived, with HFS estimating 2000 expected to be in full operation in 2025. So, are these GCCs genuinely the new face of Indian IT?
Let’s discuss:
GCCs thrive while third-party providers struggle
The rise of GCCs has been nothing short of meteoric. As third-party tech and BPO service providers navigate turbulent waters, GCCs are scaling new heights. The numbers speak volumes: HFS estimates show 1,650 GCCs established in India (growing at 11% this year), employing around 1.6 million people, with 120 new GCCs launched just in the first half of 2024 alone. HFS estimates over 2.7 million people will occupy India’s GCCs by the end of 2026, which could top 4 million staff by 2029. In addition, annual spending in GCCs will move past $50 billion this year and could almost double over the next five years.
Net-net, this explosive growth has redefined India’s tech industry and is being driven by rampant expansion across India’s leading tier 1 and tier 2 cities for talent:
The secret? Effective GCCs are much more closely integrated with their parent organizations, aligning with corporate goals, which ensures optimal resource allocation, effective project management, and a profound understanding of their parent company’s culture and objectives. In short, many global decision-makers within the Global 2000 feel much more in control over their operations in a market of rampant technological development and economic uncertainty:
GCCs are shifting the “Why India” question from Cost Arbitrage to Skills Arbitrage
The GCC model is not new (remember “captives” and Global In-house Centers/GICs), but its value proposition has been evolving significantly in recent times. Initially seen as cost-saving centers, GCCs have transitioned to a focus on skills arbitrage. India’s deep reservoir of skilled IT professionals now promises something far more valuable: cost-effective innovation at scale. This pivot has rebranded the “Why India” narrative from a mere cost-saving exercise to a strategy of substantial value creation—a vital advantage for enterprises caught in the “digital dichotomy,” struggling to balance macroeconomic challenges with the need for relentless innovation:
GCCs are making IT services sexy again for Top-Tier Indian Talent
The Indian IT services industry has long faced challenges in attracting top-tier talent, with the best and brightest often gravitating toward startups or global technology providers. Our study of 1,800 IT services employees last year revealed widespread dissatisfaction, with many feeling under-challenged and ready to jump ship (See exhibit below). The problem with the services industry is that when companies provide outsourced services for enterprise customers, it’s most often the monotonous tasks the customer can offload at scale, such as application testing, infrastructure monitoring, accounts payables or receivables.
Even sexier-sounding work, such as content moderation for social media sites or product support services, is usually very tedious after a while, especially when the services worker is just instructed to follow a standard operating procedure without any incentives to use judgment, creativity, analytical skill, or common sense. It’s no wonder staff have been quitting in droves in search of something more challenging when there is so much demand for workers to perform higher-impact work elsewhere. Now that their next job may turn out no more challenging than their current gig if there’s 30% more money for doing it, why not?
In short, employees do not like their current employers because of their lack of career growth opportunities, bureaucratic company cultures, difficulties finding the right work-life balance, and disillusionment with the company’s purpose and vision:
As you can see, close to 9 out of 10 staff want to feel more challenged (and are bored), 61% will jump to a competitor for a pay hike, and 75% believe they can easily find a job as good as the one they currently have. The only saving grace for the IT and Business services industry is that 90% of employees are passionate about the impact they can have on enterprise clients. The simple fact that GCCs offer the chance for Indian talent to get closer to global enterprises and have a more direct impact on their clients (true OneOffice) is making the GCC career option far more attractive than many of these “back office” service provider roles.
GCCs are reversing this trend. Offering up to 30% higher salaries, often more challenging roles, and opportunities to work with cutting-edge technologies and prestigious institutions, GCCs are making IT services desirable once again. This resurgence in interest is not only enhancing GCC capabilities but also elevating the entire Indian IT industry, especially during these challenging times for its traditional outsourcing market.
HFS Recommendations for Long-Term Success with the GCC Model
GCCs have rightly earned the spotlight, but to sustain their momentum, they must continue to innovate. The future is promising, but complacency is the enemy. Here’s what they need to do:
1. Embrace India’s blossoming AI talent to drive Technology Arbitrage
GCCs are accelerating India’s value proposition from cost to skills arbitrage. Now, they must embrace AI to unlock the potential of technology arbitrage, positioning themselves not just as cost-effective hubs but as epicenters of technological innovation (See below). No region in the world comes close to India to develop talent at scale, which can learn the latest GenAI and machine learning tool. The booming startup ecosystem and ambitious numbers of college graduates place India in an ideal position to dominate the future of AI development, with GCCs at the core.
If this shift is managed effectively, it will transform many GCCs from support centers to strategic drivers of global business value, supporting companies to optimize processes, predict market trends, and respond to changing consumer needs to create new revenue streams. This shift would not only enhance the competitive edge of their parent organizations but also establish many GCCs as leaders in the global technology landscape. The challenge is centered on transitioning from a people-centric model to a technology-driven one, but the rewards are immense if you can adopt the right mindset for change and innovation.
2. Benefit from a Hybrid Model of in-house capabilities AND third-party services
The future is hybrid. While 40% of Global 2000 enterprises use a hybrid model, this figure jumps to nearly 65% for those with over 15 years in the game (See below). On a long-term basis, companies are more likely to adopt a hybrid model, due to their need for greater flexibility and the ability to balance cost-efficiency with specialized expertise. A hybrid model that combines in-house capability centers with third-party services can offer the best of both worlds. This approach allows for flexibility, scalability, and access to a broader range of expertise and resources, enhancing overall service delivery and innovation capacity. The conversation should not be “In-house OR 3rd parties” but “In-house AND 3rd parties.” The hybrid model offers the flexibility and scalability that today’s dynamic business environment demands. It’s not a choice between in-house and third-party services—it’s about integrating both to create a more robust, versatile operation.
3. Make GCCs a vital part of the Corporate Innovation Agenda
GCCs are often perceived as execution engines rather than innovation leaders, including instances where GCCs are primarily tasked with implementing strategies and projects designed by the parent company rather than driving the ideation and development of those strategies. For example, a GCC might be responsible for scaling a software development project globally, but the core innovation and design decisions are made at the headquarters.
GCCs should aim higher than executing the corporate innovation agenda set by their parent companies. They should aspire to create this agenda, leading the way in identifying new opportunities, technologies, and market trends. By taking a proactive role in innovation, GCCs can become indispensable partners to their parent organizations, driving strategic initiatives and long-term growth.
The key challenge here is to establish stronger lines of collaboration between GCC leaders and the enterprise leaders in corporate. This is usually a result of legacy-minded corporations who traditionally treat Indian resources as “back office” as opposed to being part of the broader corporate mission. Smart enterprise operation leaders need to establish clear skills development programs and career paths to encourage more Indian staff to establish themselves as strategic workers forming part of global teams. This is where enterprises, in general, need to invest in a global talent model and ensure the GCC is fully integrated with the rest of the enterprise and not sectioned off as a support center.
Bottom line: It’s time to elevate GCCs from execution engines to innovation leaders
Global Capability Centers (GCCs) have become a pivotal force in the Indian IT industry, driving operational excellence and innovation at scale. However, to sustain their success and continue leading the charge in global technology services, GCCs must evolve significantly beyond their current roles.
Embracing AI and shifting towards a technology-driven model will position GCCs as epicenters of innovation rather than mere execution engines. Moreover, adopting a hybrid model that integrates in-house capabilities with third-party services will provide the flexibility and scalability needed in a dynamic business environment. Finally, GCCs should not simply implement the corporate innovation agenda but also aspire to help create it, thereby becoming indispensable partners in shaping the future of their parent organizations. The time is ripe for GCCs to transition from cost and skills arbitrage to full-fledged technology arbitrage, ensuring long-term growth and global leadership.
At HFS, we are diving deeper into this exciting GCC space. Watch out for our upcoming videocast series with GCC leaders, our GCC executive roundtable in Bengaluru, and our HFS Summit in India next February.
In the endless march toward cost savings and efficiency, enterprises have increasingly turned to generative AI (GenAI) to optimize every facet of their operations. In theory, this should lead to unprecedented productivity levels, freeing up time and resources for innovation and growth.
However, the reality of GenAI integration into the workplace reveals a paradox: while the initial productivity gains are evident, they often come with hidden costs that can offset the benefits by creating new challenges. The highest cost that must be addressed is when people become over-reliant on GenAI to develop solutions and suffer a decline in their learning capabilities.
GenAI could erode human creativity as people become dependent on the technology for basic cognitive tasks
Multiple research studies over the past couple of years clearly indicate that GenAI can automate many tasks, significantly boosting productivity in the short term; for example, 35% of leading executives across driving GenAI initiatives have already witnessed productivity and efficiency increases. However, reliance on these AI tools might inadvertently devalue or erode human creativity and heuristic skills as people become too comfortable relying on them, rather than developing their own solutions.
When individuals rely on AI to perform cognitive tasks such as data analysis, writing, or decision-making, they may sacrifice the opportunity to develop and hone these critical skills. For instance, a study from the University of Pennsylvania in a high school context found that GPT-4 improved short-term student performance in math (48% for GPT Base and 127% for GPT Tutor). However, reliance on it led to worse outcomes when access was removed, with a 17% performance drop compared to those who never had access. This dependency can erode the workforce’s intrinsic problem-solving abilities and creative thinking, which are vital for driving long-term innovation and competitive advantage.
GenAI will improve you if you use it to focus on smarter ways of achieving positive outcomes
On the flip side, one can argue that GenAI tools simply help us do things smarter, so we just become worse at the old way of doing things. The results from this University of Pennsylvania study could indicate that GenAI only diminishes our cognitive skills somewhat if we don’t refocus our brains on using our freed-up time and creativity effectively. For example, there is evidence that shows people become fitter using e-bikes than regular bikes, as they enjoy the experience more and end up cycling for longer, ultimately burning more calories and becoming physically fitter. Or in some cases people who never used to cycle now engage in the activity as it’s so much more enjoyable and efficient.
AI’s potential impact on creativity is profound
AI’s ability to generate content and ideas could also discourage individuals from producing original work, leading to a loss of creative skills. In creative fields such as art, writing, and design, the overuse of AI-generated outputs can result in a decline in the unique human touch that characterizes these disciplines. As people become more dependent on AI for creative tasks, the skill sets required for these activities may diminish, stunting the richness and diversity of human creativity.
In a worst-case scenario, over-reliance could make enterprises vulnerable to disruptions or threats; if employees are accustomed to handling complex tasks, a failure or limitation in the AI system could leave them ill-equipped to manage these challenges independently. The initial productivity gains from AI could thus be offset by a decline in human capability, leading to a net negative impact on the organization’s long-term innovation and adaptability.
Employee experience also takes a hit when organizations hyper-focus on productivity outcomes
An HFS study found that more than half of the 550 executives sampled (52%) recognize an obsession with productivity as problematic. When asked about the potential risks of this hyper-focus on productivity, 44% indicated that the overemphasis leads to employee dissatisfaction, burnout, and declining morale:
This obsession with productivity can create a high-pressure environment where employees feel constantly monitored and evaluated, leading to increased stress and a sense of being undervalued. In the long term, such an environment can result in higher turnover rates, as employees seek workplaces that prioritize their well-being and provide a more balanced approach to productivity and innovation.
Organizations must strive toward a balanced human-AI symbiosis to mitigate the productivity paradox
In the late ’60s, Douglas Engelbart, in his work “Augmenting Human Intellect: A Conceptual Framework,” introduced the idea of human-AI symbiosis, where AI systems enhance human capabilities rather than replace them. This concept is critical to understanding the productivity paradox in GenAI adoption. While GenAI technologies promise significant productivity gains by automating complex tasks, the true potential of these technologies is realized when they are used to augment human intellect and creativity. In practice, enterprises should focus on integrating GenAI to complement and enhance human skills rather than create a dependency that could undermine long-term innovation and adaptability.
Ultimately, the productivity paradox arises when organizations fail to achieve this symbiosis. Instead of merely automating tasks for efficiency, enterprises should leverage GenAI to empower employees, providing them with tools that extend their capabilities and foster a more innovative and agile workforce. This approach helps mitigate the risks of skill degradation and dependency, ensuring the workforce remains resilient.
Recommendations to drive human-AI symbiosis and mitigate the productivity paradox:
Training and development: More than one-off training will be required to ensure that AI tools complement rather than replace human skills. Invest in continuous training programs to help employees develop and maintain critical cognitive and creative skills alongside AI.
Conduct “show and tell” GenAI training workshops: Nothing is more effective than having your staff demonstrate their active use and enjoyment of GenAI in collaborative group settings. This encourages more uptake, smarter use of the tools, and real-time sharing of best practices.
Human-AI collaboration: Encourage a collaborative approach where AI handles repetitive tasks, and humans focus on complex problem-solving and creative work.
Encourage experimentation: Create an environment that values experimentation and risk-taking, allowing employees to explore new ideas without fear of being judged solely on productivity metrics.
Reward creativity: Implement recognition and reward systems that celebrate creative solutions and innovative thinking.
Work-life balance: Promote policies that support work-life balance to reduce stress and burnout. Flexible working hours and remote work options can help achieve this.
Employee feedback: Regularly solicit feedback on employees’ experience with AI tools and use their input to make adjustments that improve their work environment and job satisfaction.
Invest in continuous upskilling: Prioritize ongoing training and development to mitigate the skills gap created by the rapid adoption of GenAI. This ensures employees are adept at using AI tools and capable of critical thinking and problem-solving with these tools.
The Bottom Line: By fostering a symbiotic relationship between humans and AI, enterprises can achieve sustainable productivity gains that drive long-term growth and innovation
In essence, the productivity paradox is the realization that if the drive for efficiency sidelines the human workforce and what is required to nurture them to use AI effectively, the pursuit of productivity and efficiency gains will be compromised.
Organizations can mitigate these risks by promoting balanced AI integration, fostering a culture of innovation, and focusing on employee well-being. Ensuring AI tools complement human skills, encouraging experimentation and creativity, and supporting work-life balance can help maintain GenAI’s long-term benefits without compromising human capabilities and employee satisfaction.
Remember all the excitement about the Rabbit R1, and how this was supposed to signal the demise of the appstore and the onset of Large Action Models? Where we were no longer going to be held hostage by app providers refusing to open up their APIs or be forced to work through the dysfunction and poor integration of many painful subscriptions?
Remember the promises that all we had to do was talk to this little orange thing and it would execute pretty much anything we wanted? And all we had to do was drop $199 on the device to experience an AI-driven change to our lives where these effortless experiences would change everything for the better…
Rabbit.tech caused such a stir at the 2024 CES event, with Founder Jesse Lyu claiming his firm Rabbit could totally disrupt the app store in a similar fashion to how ChatGPT is disrupting web search. Even Microsoft CEO Satya Nadella has described the Rabbit’s launch of its R1 hardware as the most impressive since Jobs’ historic iPhone launch in 2007.
Source: YouTube, 2024
Well, after making us wait almost six months, the little red devices have finally arrived for a $199 price tag.
The reality is the device only supports only supports Spotify, Apple Music, Midjourney, Suno, Uber, and DoorDash. Do I really need to listen to music on this orange thing and order a pizza with it? What about sending emails, texts, whatsapps, calendar invites, or anything remotely useful? This is the response I received from Rabbit customer support:
The Bottom-line: Beware of AI snake oil, as some of it is very slippery indeed. Rabbit promised us freedom from app lock-in and all we got was more lock-out
I am sure there are may reasons why I now have a useless orange device taking up space on my desk and $200 missing from my bank account, but the delta between the device Jesse was selling and what I ended up with is scandalous. I can warn you about salesmen selling you AI dreams that appear too good to be true, but I know you are already probably very very wary!
