Growth in the tech services sector has slowed
Something important is happening in tech services. Before COVID, the sector was humming along at 4%–5% annual growth. Now it’s slowed to 2%–3%. Margins have shrunk by over 200 basis points. Valuations have dropped back to where they were before the pandemic. That’s not just a post-crisis correction, it’s a structural shift. Market dynamics are changing, and the rules that worked for the last decade don’t necessarily apply anymore.
Many forces are pushing against the traditional growth model, automation, geopolitical uncertainty, shifting demographics. A large part of routine tech services is becoming commoditized or automated out of existence. If firms continue operating like it’s still 2019, they’re facing up to 30% revenue loss and risk watching enterprise value cut in half over the next five years. EBIT margin hits from discounting and pricing pressure will only accelerate that drop.
That’s not doom and gloom, it’s clarity. Every company hits these inflection points, where what got them here won’t get them there. The smart move now is not to optimize the past. It’s to realign around where growth is going and move with more speed and less friction.
AI as the primary disruptor and catalyst for opportunity
Artificial Intelligence is not a tool bolted onto existing systems. It’s crossing the threshold into becoming core infrastructure for how companies operate. Whether we’re talking about large language models, edge inferencing, or AI-driven software development, this is one of the biggest shifts we’ve seen since the rise of the internet.
What’s interesting now is that the actual application of AI is scaling fast. We’re seeing it speed up app modernization that once took years. Industries running legacy systems built on decades-old code, like parts of banking and government, now have a path to translate that logic into modern programming with less effort. We’re talking about 200 to 800 billion lines of Cobol that can be modernized using AI. That’s not a small opportunity.
As AI moves from cloud to the edge, demand for low-latency models and smart hardware is rising. This is fueling massive data center growth, with big investments in compute, cooling, and chip design. Companies that provide services around these areas, data pipelines, validation layers, chip architecture, can build major revenue lines if they move early.
This is what every executive team needs to watch. AI isn’t just changing parts of what we sell, it’s about to define how we build, deliver, and scale every solution moving forward. Betting on this shift isn’t risky. Waiting is.
Expanding role of tech services in end-to-end enterprise transformation
Technology services are becoming embedded across the full spectrum of business operations. Companies no longer see tech as just support, it’s now integral to how they rethink their entire workflows. From the front office to the back end, every process is being evaluated for redesign through an AI-enabled lens.
This kind of transformation doesn’t happen by outsourcing a single task. It requires multiservice capabilities working in sync, technical platforms, business process knowledge, design thinking, industry-specific expertise. Take the shift happening in how banks process mortgage applications or how insurers manage claims. These aren’t quick wins. They require full integration of AI, automation, platform architecture, and intelligent operations tied to clear business outcomes.
Customers are looking for more than automation. They want simplified processes, better performance outcomes, and speed. To deliver that, service providers need end-to-end control of the solution lifecycle. That means bringing data to the center, data that is modern, use-case specific, and AI-ready. Without that, AI doesn’t scale, and transformation stalls quickly.
Implementation isn’t the end goal. Enterprises want measurable value, reduction in cycle time, improved decision accuracy, and system-wide responsiveness. If you’re not delivering these outcomes, someone else will.
Impact of economic nationalism and changing global regulations
The geopolitical environment has changed. Global supply chains are under pressure from trade tensions, tariffs, and tightened visa policies. Nations are prioritizing domestic capability building and regional autonomy. While this has disrupted traditional delivery models dependent on cross-border labor and offshore cost advantages, it has also opened new opportunities.
We’re seeing investment flows shift, towards Japan, the Middle East, and Southeast Asia, as governments push for digital infrastructure, cloud adoption, and secure tech ecosystems. At the same time, blockchain adoption is gaining traction as states formalize policies around stablecoins and digital assets. This makes the regulatory environment more predictable, which is exactly what enterprise clients are looking for.
The push for domestic resilience also means service providers must localize talent more aggressively. The rising cost and complexity of H-1B and other international visa processes have made this shift urgent. But the upside is clear, companies that anticipate these changes and structure their delivery models accordingly will gain better access to local contracts, proximity-based partnerships, and regulatory buy-in.
This isn’t about rejecting globalization. It’s about adapting to the new structure of it. Service firms that stay agile and align with these regulatory realities will protect margins and capture clients seeking regional focus and execution reliability.
Demographic shifts and an aging workforce alter the talent landscape
In many developed economies, especially Japan and across Europe, the available workforce is shrinking due to aging populations. This is creating a long-term imbalance between labor supply and business demand. The result is increased operating friction. Companies are being forced to do more with fewer people.
For tech service providers, this changes how delivery gets done. With fewer skilled workers available and demand still rising, the only viable path is to push harder on automation, AI agents, and robotics. These technologies are no longer about optimization, they’re necessary infrastructure to address labor gaps at scale.
There’s also a shift happening in what kind of talent wins. It’s less about scale and more about capability. Service firms will need engineers and consultants who combine technical literacy with context awareness, people who can solve real enterprise problems using modern tools, rather than just process transactions.
This is not a temporary phase. As birth rates remain low in many economies and job protections increase, service providers must rethink training, hiring, and career pathways. Leveraging technology to replace or augment work should become a first-line strategy, not a contingency plan. Companies that hesitate will simply fall behind as delivery becomes less efficient and harder to scale.
The global energy transition drives new demand for tech services
The shift toward clean energy and more intelligent infrastructure is rewriting financial priorities in energy-intensive industries. Oil and gas, utilities, and manufacturing firms are redirecting capital into grid modernization, low-emission technologies, and new energy sources, including a renewed push around nuclear.
Tech service providers have a major role here. Powering AI-driven data centers, electric vehicle platforms, and industrial automation requires big upgrades to energy supply, resilience, and system-wide intelligence. These infrastructure investments demand new digital systems behind the scenes, process control software, intelligent monitoring, demand forecasting, and integration platforms.
This isn’t niche. Data centers alone are driving hundreds of megawatts of new energy demand globally. The systems supporting this growth need to be smarter, more automated, and more efficient. At the same time, green infrastructure projects, like next-gen battery storage or decentralized energy systems, create sustained demand for software and services that can tie everything together.
Business leaders in tech services should see this transition not just as a challenge around cost and regulation, but as a new long-cycle growth driver. Enterprises will need help designing, building, and optimizing digital systems that align with shifting energy economics. If you’re positioned on the digital side of this transition, the demand is there. It’s real.
Intensifying competition from AI-native firms and hyperscalers
The competitive environment in tech services is changing fast. AI-native platforms like OpenAI and Palantir, along with hyperscalers such as AWS, Microsoft, and Google Cloud, are now offering services that overlap directly with traditional IT service models. These players move quickly, deliver at scale, and bring deeply integrated platform solutions.
The real shift is in how services are delivered. Instead of customized, project-based engagements, these firms offer repeatable, AI-powered solutions that customers can deploy faster, with more predictable outcomes. That compresses the margin space for traditional service providers and raises customer expectations.
This isn’t just more competition, it’s a new category of competitor. These companies operate with deep vertical integration, control their products, and have vast ecosystems. That speeds up delivery and lowers cost. If you’re a traditional tech services firm and you’re not moving toward more scalable, AI-infused offerings, you’re falling behind.
Winning in this environment means redefining service portfolios. You need to streamline delivery, modularize solutions, and invest in core platforms that scale. Holding onto bespoke legacy models will only reduce competitiveness in a market moving toward speed, efficiency, and automated intelligence.
Embracing eight fundamental imperatives for transformation
There are eight things that tech service firms need to do right now if they want to lead in this market. First, shift strategy toward high-impact, niche opportunities, what we call micro-battles. These sit at the intersection of specific industries, geographies, and spending dynamics. Success in these areas depends on owning both the technology and the domain knowledge.
Second, transition from isolated capabilities to integrated, multiservice solutions. It’s not about selling a tool, it’s about delivering a result. That means combining service design, software development, AI-enabled ops, and domain expertise into one packaged, outcome-oriented service.
Third, reset your go-to-market motion. Sales teams need to become strategic advisors, not product pushers. That requires new skills, tighter integration with partners, and continuous learning loops between product, delivery, and client-facing teams.
Fourth, platform-based delivery must become the core operating model. Services need to be consistent, scalable, and metrics-driven. This supports the transition to value-based pricing, where you’re compensated for the results clients see, not just the hours you sell.
Fifth, talent strategy has to change. The old pyramid model of labor-intensive delivery no longer scales. You need streamlined, expert-led teams that work across cultures and geographies. Career paths must evolve, and employer value propositions must adapt to Gen Z expectations around flexibility and purpose.
Sixth, culture needs a reset. Move away from legacy hierarchies and siloed structures. Adopt flatter, faster teams supported by empowered frontline decision-making. This isn’t just about productivity, it’s about responsiveness.
Seventh, upgrade your partnership play. Clients expect integrated ecosystems. That means forming strategic alliances where you co-create offerings, co-invest in IP, and go to market together in a coordinated way.
Eighth, make M&A a core operating discipline. Acquisitions, especially in AI platforms and data services, can be the fastest way to scale capabilities. But it only works if your integration playbook is strong.
Firms that move on these imperatives now will separate themselves from the rest. Bain’s research shows they can grow 8% to 10% annually, hold or grow margins, and improve revenue multiples by as much as 3 to 3.5 times. The return on action is significant, but only for those willing to move early and stay committed.
Necessity of internal efficiency and disciplined capital allocation
Competing in today’s tech services environment requires more than new offerings. It takes internal alignment and disciplined execution. If you’re serious about transformation, you need capital, and you get that by running leaner, faster, and with better financial control.
Most firms still carry operational weight from pre-AI structures. That includes slow, manual processes in HR, finance, procurement, and product delivery. These aren’t just inefficiencies, they’re barriers to scalability. Applying AI internally, across non-customer-facing functions, is now essential. This goes beyond productivity, it directly frees up margin, unlocking 200 to 300 basis points that can get reinvested into talent, product, or M&A.
Fixed-price delivery also needs improvement. That means less variability, better scoping, and more granular control of outcomes. Delivery models have to move away from people-heavy, service-line siloed structures and shift to platform-supported engagement. Efficiency at the core enables strategic investment at the edge.
Executives need to ask whether their operating model supports velocity or slows it down. Eliminating low-value complexity and reallocating core spending allows firms to fund innovation instead of financing maintenance. That’s the difference between staying afloat and achieving breakout growth over the next five years.
Immediate action is critical to avoid value erosion
The window to act is short. AI, energy disruption, demographic reversal, and regulatory shifts are all converging at once. Firms that stay flat-footed are exposed to serious value erosion, up to 50% enterprise value loss, according to Bain’s latest research. That is not a projection for 10 years from now, it’s unfolding in this five-year cycle.
But the upside is equally clear. Companies that commit fast, leaders who make concentrated strategic bets and execute with focus, can capture outsized growth. Bain’s data shows that forward-leaning firms in this space are projected to grow 2x faster than the market, while expanding both margin and revenue multiples.
The defining differentiator now is execution under uncertainty. The macro conditions will continue shifting, what matters is how decisively a company adapts. That applies to everything: re-prioritizing markets, digitizing delivery, upgrading teams, and evolving the core business model. Making bold moves while others hesitate is where the advantage compounds.
For C-suite leaders, this means treating this transformation moment as non-optional. Hesitation doesn’t preserve value anymore. It burns it. Acting quickly and with clarity is the only path forward.
In conclusion
Tech services aren’t broken, they’re out of sync with where value is now shifting. Growth hasn’t disappeared; it’s just moving to different parts of the map. AI isn’t optional. Regional dynamics aren’t temporary. Workforce changes aren’t a blip. These are structural shifts. Treating them as such is the difference between fadeout and breakout.
For decision-makers, this is not a time to hedge. It’s a moment to allocate capital with precision, align teams around execution, and move fast on bets that accelerate learning and scale. Strategy, talent, delivery, and pricing all need a reset, and done right, that reset unlocks growth well above market pace.
The next few years will create a wide gap between those who adapt fast and those who don’t. The winners won’t just respond, they’ll redefine what tech services can deliver. If margin, relevance, and valuation matter, now is the time to build what’s next.
