By Krunal Patel, Managing Director, NTT DATA Business Solutions
Math is breaking enterprise IT in 2026. Bain & Company studied 24,000 transformation initiatives and found 88% failed to achieve original ambitions. Poor execution? One prime reason was poor preparation for the future.
Today, companies average multi-year transformation timelines while market conditions shift in quarters. By the time transformation completes, the problem usually evolves beyond recognition. This timeline has only accelerated with the advent of AI.
The industry is changing as we speak. At present, business verticals need to pivot within a quarter, sometimes even weeks, or risk becoming irrelevant before the next board meeting – a modern-day dinosaur.
The AI acceleration problem
MIT’s recent study quantifies the current crisis. 95% of enterprise GenAI pilots deliver zero measurable P&L impact. S&P Global estimated 42% of companies abandoned most AI initiatives in 2025, double the rate from just a year earlier.
A survey by Horváth of 200 SAP customers further revealed that 65% of enterprises missed quality targets and 55% exceeded budgets on their S/4HANA migrations. Projects took 30% longer than planned.
The devil lies in the details. For instance, MIT found that pilots fail not because models don’t work, but because organisations build them isolated from operational workflows. When pilots reach production readiness, business priorities have already shifted. Horváth, meanwhile, discovered the primary culprit was scope expansion mid-transformation as business requirements evolved faster than implementation could keep pace.
This creates a paradox when you consider that enterprises will spend roughly $6.08 trillion globally on digital transformation projects in 2026. Yet, almost nine in ten of these initiatives will fail to deliver expected value.
Organisations are still architecting for stability in an era that demands perpetual motion.
Decision velocity, the metric that matters
Decision velocity, the speed at which you make correct, governed decisions when conditions change, has become the dividing line between market leaders and laggards. McKinsey’s analysis of 440 large enterprises revealed organisations in the top quartile for decision velocity achieve revenue growth 4-5 times higher than their peers.
Take, for instance, how fintech companies and banks operate. Fintech companies ship product updates 3-4 times weekly while traditional banks manage quarterly releases. Banks typically optimize systems for deployment speed while leaving organisational decision-making untouched. They can push code to production in minutes but require three months of approvals to decide what code to push.
Then, real adaptiveness becomes structural, not technical.
But what does structural adaptiveness look like in 2026? It looks like an enterprise designed the way modern products are designed: modular, interoperable, and instrumented while being ready to reconfigure without ripping out the foundation.
The Adaptive Enterprise
In practice, structural adaptiveness comes down to five repeatable moves that keep the core resilient while letting teams reconfigure processes, products, and decisions at the pace of the market.
1. Build a composable core
“Build once” does not mean “build big.” It means standardizing the few things that should never be reinvented such as identity, master data, policy, integration patterns, observability, security, and process guardrails. Then, keep everything else modular. You can think of everything as LEGO blocks rather than poured concrete. Small, reusable capabilities snap together into new offerings, new channels, and new workflows with minimal rework.
2. Go integration-first because AI can’t scale inside silos
Most pilots die because they’re clever demos floating outside the flow of work. The adaptive enterprise flips the sequence: integrate first, automate second, and then apply AI. Start with APIs, events, and canonical data contracts that connect systems of record to systems of engagement. When your architecture is event-driven, change travels at the speed of business. For instance, a supply disruption may trigger reallocation or a service incident may reroute work without a project kickoff every time.
3. Embed “real-time decisioning” as a product
In 2026, the key differentiator is a decision layer that is explicit, governed, and continuously improved. Rules, models, and human approvals work together seamlessly here. A great thought exercise is to ask yourself, “In this workflow, can the organisation decide within minutes, with auditability and clear accountability?”
4. Standardize the end-to-end processes that matter most
Adaptiveness is consistency where it counts. Develop digital, end-to-end processes like order-to-cash, procure-to-pay, record-to-report, hire-to-retire, etc. across lines of business, so teams can pivot smoothly when required. Standard processes create shared language, shared data, and shared KPIs, making it far easier to deploy automation and AI that actually moves P&L.
5. Use a Business Technology Platform to keep the core clean and the edges fast
A Business Technology Platform becomes a strategic control plane. It manages all your integrations, workflows, automations, analytics, and extension development, letting you innovate at the edge without destabilizing the core.
Instead of customising your ERP into a dead-end, you extend responsibly by reusing services, enforcing governance, and accelerating delivery with consistent patterns.
Lastly, in 2026, winners won’t “transform” every few years. They’ll reconfigure every few weeks confidently, securely, and at scale. That’s the new advantage. Build once, pivot often, and make change a built-in feature of the business.