Info-Tech Research Group: AI Delivers Limited Returns Without Process Redesign, Not Just Task Automation

Most AI projects are failing to move the needle. According to Info-Tech Research Group, organizations are plugging AI into individual tasks instead of rethinking the workflows that actually drive business results — and the returns are suffering for it. A new blueprint from the firm aims to fix that.
The numbers are stark. Info-Tech Research Group cites research showing that 95% of enterprise generative AI pilots have produced zero measurable impact on company financials. Only about 2% of organizations have fully scaled AI deployments. The firm says the core problem is simple: organizations are automating old processes instead of building new, better ones.
Info-Tech calls the current approach "surface-level automation." Companies take an existing workflow and drop AI into one step. The rest of the process — the decisions, handoffs, and bottlenecks — stays the same. Info-Tech Research Group says this is why AI investments feel busy but deliver little. It is the modern version of replacing a steam engine with an electric one without changing the factory floor.
The broader track record backs that up. The RAND Corporation has reported an 80.3% failure rate for AI projects overall, according to Info-Tech Research Group. Analysts at Morningstar describe AI as having moved from a "strategic ambition" to an "execution challenge." The easy wins from simple task automation have largely been claimed. What remains is harder structural work.
The new blueprint, titled "Reimagine Business Processes With an AI-First Approach," gives IT, business, and operations leaders a three-step framework. Step one is Discover — find the highest-value processes to target. Step two is Diagnose — map where current workflows break down. Step three is Design — build a future-state workflow with AI at the center, not bolted on the side, according to Info-Tech Research Group.
The blueprint also tackles a coordination problem. Info-Tech Research Group found that business, IT, and operations teams typically lack a shared language for deciding which processes are ready for AI redesign. Without that common framework, teams end up chasing different priorities. The blueprint gives all three groups the same starting point.
The stakes are rising fast. A new wave of "agentic AI" — AI that can plan and carry out multi-step tasks on its own — is emerging. But experts warn it only works if the underlying process is built for it. Dropping an autonomous AI agent into a human-centric workflow creates friction, not efficiency. Info-Tech Research Group frames this as the central reason process redesign must come before AI deployment, not after.
Agentic AI and process redesign together are projected to create nearly $450 billion in value by 2028, according to research cited by Info-Tech Research Group. But that payoff is reserved for organizations that move beyond pilots. Research Director Andrew Kum-Seun has argued that teams must evolve "beyond siloed, task-oriented delivery" into cross-functional groups that "co-own outcomes."
Process redesign does not just change software — it changes jobs. Info-Tech Research Group notes that workers will shift from doing tasks to managing the AI that does those tasks. Organizations that skip reskilling risk being left with a workforce that cannot operate the new systems they are building.
The infrastructure demands are just as real. AI-driven process redesign is pushing massive new loads onto data centers. Goldman Sachs projects a 160% rise in AI-driven electricity demand. By 2030, data centers could consume 10% of all U.S. electricity — four times the current share. Info-Tech Research Group frames this as a sign that AI is no longer a pilot project. It is a core operating reality that demands foundational change, not incremental tweaks.
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