Transformation Is No Longer Technology-First — It's About Redesigning Work

TL;DR

92% of companies plan to increase AI investment over the next three years, but only 1% describe themselves as mature in how they integrate AI into their ways of working (McKinsey, 2025). The constraint is no longer access to technology — it’s the organization’s ability to redesign work, roles, and operating models around it. Transformations that install new tools without redesigning the operating model around them are part of the well-known statistic that 70% of transformations fail.

Why this matters now

For years, organizations treated transformation as a technology challenge: choose the right platform, digitize the process, automate what you can, and the business becomes faster and more efficient. That approach made sense when the biggest gains came from replacing manual work or consolidating systems. It is no longer enough.

Over the last 12 months, one theme has become impossible to ignore across transformation research: the real constraint is no longer access to technology — it’s the organization’s ability to redesign work, roles, and operating models around it. McKinsey’s 2025 workplace research found that 92% of companies plan to increase their AI investment over the next three years, but only 1% describe themselves as mature in how they integrate AI into their ways of working. The conclusion is telling: the challenge is not technical, it’s organizational.

That gap matters because it reveals that most organizations are not struggling to choose tools — they are struggling to rethink how work gets done. Transformation has moved beyond system implementation into the much harder territory of workforce redesign: task allocation, team structures, management layers, decision rights, capability models, governance, and culture.

BCG made this point directly in 2025, arguing that AI is changing not only tasks but also the talent companies need and the way teams interact. Many organizations remain in an early, tool-based phase of adoption, while the next step is workflow transformation and, eventually, agent-led orchestration where humans steer and AI handles more end-to-end execution. That shift is bigger than a technology rollout — it is a redesign of the operating model itself.

Only a redesigned operating model realizes the gains

AI is bringing real productivity gains to organizations, but only a redesigned operating model can realize those gains across roles, teams, governance, and performance expectations. Otherwise the gains stay isolated and the organization captures only a fraction of the available benefit.

Recent research shows that successful operating model redesign depends on four themes: leadership alignment, rewiring core processes, significant investment in people, and sustained focus on a high-performance culture. The most successful transformations are not simply the ones that install new tools — they are the ones that redesign the organization around value creation.

This is where many transformation programs stall. Leaders approve a strategy, fund a technology program, and expect the organization to adapt naturally. The real operating model remains largely untouched: teams keep operating the same way, managers are not fully invested in the change, and processes are only partially rewired. The result is part of the well-known statistic that 70% of all transformations fail.

BCG’s 2025 AI at Work findings show that regular AI use among frontline employees has stalled at 51%, even though leaders and managers use it far more frequently. Employee positivity toward generative AI rises from 15% to 55% when there is strong leadership support — sponsorship matters. Regular use is also much higher when workers receive at least five hours of training, plus in-person support and coaching. Transformation does not scale through tools alone. It scales through support, reinforcement, and leadership behavior.

Management should shift its focus

The more useful question is no longer “what technology are we deploying?” It’s “how does work need to change to benefit from it?” That question has serious implications.

Redesign work at the task level. Many organizations still approach AI as a productivity layer added to existing jobs. But once AI can support analysis, drafting, testing, planning, or workflow orchestration, the shape of work itself changes. Some tasks shrink, others accelerate, and some become more supervisory than manual.

Redesign management, not just teams. If systems can synthesize information and prepare decisions automatically, managers need to contribute more through judgment, coaching, prioritization, and exception handling. Transformation should change not just what teams do, but what leadership looks like.

Treat adoption as a performance lever. Organizations scale transformation through support, reinforcement, and leadership behavior — not tools alone. The goal of any transformation is to turn new ways of working into habit.

We are facing the rise of what Microsoft calls Frontier Firms (Microsoft’s 2025 Work Trend Index) — organizations built around hybrid teams of humans and agents, relying more on on-demand intelligence and AI-enabled work orchestration. The implication is clear: management is shifting from supervising tasks to directing systems of work. This will affect middle management in particular. Traditional managers were rewarded for coordination, review, and control; if AI increasingly handles synthesis and routine decision preparation, managers need to contribute more in judgment, coaching, and stakeholder alignment.

What leaders should ask

• Which workflows need redesign first?
• Which roles will change meaningfully over the next 12 to 24 months?
• What should managers stop doing, start doing, or delegate to systems?
• What does success look like beyond adoption counts?

So what does this mean for leaders?

A practical starting point is to stop treating workforce transformation as a downstream effect of technology transformation. It should be designed alongside it:

• Redesign around workflows, not functions. The biggest gains now sit inside cross-functional workflows, especially where handoffs, delays, and approvals slow delivery.
• Treat roles as dynamic, not fixed. Revisit what roles are actually for, rather than waiting for job descriptions to become outdated.
• Build management systems for hybrid work between people and AI. Accountability, review, decision rights, and quality assurance all need to be rethought.
• Invest in people with the same seriousness as technology. Capability building and manager enablement are no longer side activities.
• Redefine transformation success metrics. Track workflow performance and role redesign, not just deployment and adoption counts.

Technology still matters. But the organizations that pull ahead will not be the ones with the most tools — they will be the ones best at reshaping the human system around them. Workforce and operating model redesign is not a side conversation in transformation anymore. It is the transformation.

From the field: This is the exact challenge I led on a Tier 1 UAE bank’s workforce transformation program — redesigning a target operating model and redeploying and retraining 100 staff into new roles, rather than simply rolling out new systems. Read more in Services: Transformation & Target Operating Model Design.