Every year, large companies spend millions on digital transformations that look great in slide decks but change very little on the ground. Drawing on more than two decades of experience across global technology services, cloud platforms, and enterprise software, including leadership roles at AWS, Google Cloud, and Kyndryl, Pankaj Kumar has observed a recurring pattern. In most cases, these projects do not fail because the underlying technology is broken. They fail because the people and systems meant to run them are rarely pointed in the same direction.
Instead of looking for a magic software fix, Kumar argues that leaders need to look at how their organizations operate day to day. When corporate strategy pulls one way while sales incentives and delivery teams pull another, execution stalls out. Fixing that problem requires straightforward management rather than more technical complexity.
Fixing the Alignment Gap
When large companies try to scale up their systems, they usually assume their biggest challenge will be engineering. But after two decades in enterprise IT, Kumar has seen that technology is almost never the real bottleneck. “My experience has taught me that ‘Scale is rarely a technology problem; it is an alignment problem,’” he says. “Over the past two decades, I have worked across global services organizations, hyperscalers, and technology businesses, and the pattern has been remarkably consistent: organizations do not struggle because they lack ideas. They struggle because strategy, incentives, and execution are moving at different speeds.”
This disconnect becomes obvious when different teams are rewarded for different things. A sales group might be pushed to close deals quickly, while the operations team is measured purely on cutting costs. When those targets clash, the whole project slows down regardless of how much money leadership invested. As Kumar explains, “A transformation can have executive sponsorship, world-class technology, and significant investment behind it and still stall if the people responsible for selling it, delivering it, and operating it are measured against different outcomes.” The solution is not to pile on more meetings or create new committees. Instead, senior leaders have to get everyone focused on the same clear results. “At scale, the leader’s job is therefore not to create more initiatives. It is to create clarity,” Kumar points out. “What business outcome are we trying to change? Who owns it? How will we measure progress? And what must be true across product, sales, partners, delivery, and operations for that outcome to happen?”
Moving Past Simple Migration
This lack of clarity is especially common in cloud migrations. Many organizations spend months planning a technical move and building a solid business case. But once the work starts, teams often get so caught up in the mechanics of moving data that they forget why they started the project. The migration becomes a check-the-box IT task instead of a business improvement. Kumar sees this as the exact point where most cloud strategies fall apart. “The breakdown usually occurs in the space between migration and transformation,” he explains. “Many cloud strategies begin with a technically sound architecture and a compelling business case. But somewhere along the journey, the program becomes focused on moving workloads rather than changing the economics or capabilities of the business.”
To avoid that trap, leaders need to track real business results rather than IT activity milestones. Moving servers to a new provider does not help a company if customers and employees see no benefit. “Migrating 100 applications is an activity metric,” Kumar points out. “Faster product releases, lower operating costs, greater resilience, better customer experience, or the ability to enter a new market are business outcomes. The distinction matters.” Moving to modern infrastructure also means changing old work habits. If a company keeps its legacy approval processes and security steps, it simply ends up paying more for the same slow operations. “Another common problem is that enterprises underestimate the operating-model change required,” Kumar says. “Moving technology to the cloud without changing engineering practices, governance, financial management, security processes, and decision rights can simply recreate the old environment on a new platform.”
Focusing on Business Outcomes
To make sure technology investments really pay off, Kumar advises executives to start with business pain points rather than new software. Instead of looking for places to install new tools, leaders should ask where their teams are struggling today. That shifts the focus away from technical hype and puts it on practical problems. “I encourage leaders to start with the business decision, not the technology,” Kumar says. “Instead of beginning with ‘Where can we deploy cloud or AI?’ ask which decisions, processes, or customer experiences are currently too slow, too expensive, or too inconsistent? That immediately makes the conversation much more concrete.”
From there, every project should be tied directly to a few clear financial or operational goals. If a team cannot explain how an investment will help the business, the project should not get funded yet. “From there, I like to establish a direct line between investment and a small number of measurable outcomes: revenue growth, margin improvement, productivity, speed, customer retention, risk reduction, or capital efficiency,” Kumar explains. “If that connection cannot be articulated clearly, the initiative probably needs more work before it needs more funding.” Shared accountability between IT and business leaders is just as important. When technology teams are left to run a project alone, business units rarely take ownership of the final results. “The second discipline is establishing accountability. Transformation becomes difficult when technology owns implementation but nobody clearly owns the business outcome,” Kumar says. “The strongest programs bring technology, operations, and business leadership together around the same measures of success.”
Redesigning Processes for AI
This focus on practical value is becoming critical as companies look at artificial intelligence (AI). Over the past couple of years, most businesses have been busy testing AI chatbots and individual tools. But executive teams and boards now want to see real economic returns on that spending. For Kumar, the answer is for companies to look past small productivity tweaks and start redesigning how work gets done.
“It changes the conversation from AI adoption to business redesign,” Kumar explains. “The first phase of enterprise AI was understandably dominated by experimentation: models, copilots, proofs of concept, and productivity use cases. The next phase will be much less forgiving. Boards and chief executive officers will increasingly ask a very straightforward question: ‘What changed in the economics of the business because of AI?’”
Saving a single employee a few minutes a day rarely moves the needle for a large business. The real value comes when entire workflows are rebuilt so that people, data, and software work together smoothly. “That means the unit of transformation has to become larger than the individual use case,” Kumar says. “If AI saves an employee 10 minutes but the surrounding process remains unchanged, the enterprise may never capture the value. The bigger opportunity comes when organizations redesign workflows so that people, data, and AI agents work together and entire processes become faster, more autonomous, or fundamentally less expensive.”
In the end, simply buying the latest software will not be enough to stay competitive. What matters is how well a company rebuilds its operations around the tools it has. “Technology creates potential. The operating model converts that potential into economics,” Kumar says. “The next competitive advantage will not come from having access to AI. Almost everyone will have access. It will come from redesigning the enterprise around it faster than everyone else.”
Follow Pankaj Kumar on LinkedIn for more insights on enterprise execution, cloud transformation, and scaling AI strategy across global organizations.
Disclaimer: The views expressed in this article are those of Pankaj Kumar personally and do not necessarily represent the views of his current or former employers.
