After the hype, a quieter story is taking hold inside big companies: many are not seeing meaningful return on investment from generative AI so far. And as consumer growth cools, expect AI vendors to push harder into business customers in 2026, selling not magic—selling measurable outcomes.
What’s behind the ROI gap?
1) Pilots don’t equal production
A lot of gen-AI work is still stuck in proof-of-concept mode: flashy demos, limited rollouts, and “innovation theater” that never becomes a core workflow.
2) Costs are easy to count; benefits aren’t
Licenses, cloud compute, security reviews, and staff time show up immediately. Productivity gains often show up slowly—or not at all—especially when teams are still learning how to use the tools well.
3) Data is messy and access is hard
Gen-AI is only as useful as the information it can safely reach. Many firms have scattered systems, inconsistent documents, and strict access controls—making “ask the company anything” much harder than it sounds.
4) Risk and compliance slow everything down
Legal, privacy, and security teams aren’t being difficult for fun. They’re trying to prevent sensitive leaks, copyright issues, and untraceable decision-making. The guardrails are necessary, but they add time and complexity.
5) Workflow change is the real work
The biggest unlock isn’t “add a chatbot.” It’s redesigning how work gets done—approvals, handoffs, templates, QA, and accountability. That’s organizational change, not software installation.
What companies are doing differently now
The more grounded approach looks like this:
- Fewer moonshots, more specific use cases (support deflection, sales enablement, document drafting, coding assistance, claims review)
- Human-in-the-loop processes where output quality actually matters
- Clear metrics: time-to-resolution, conversion rate, error reduction, cost per ticket—no more “engagement” as the main KPI
- Stronger governance: approved tools, approved data, approved prompts, logging and monitoring
Why 2026 may tilt toward “business AI”
As vendors lean harder into enterprise customers, expect:
- More “AI-as-a-feature” inside existing business software (instead of standalone chat tools)
- Pricing that tries to map to outcomes (seats + usage + premium security tiers)
- Heavy emphasis on compliance, data controls, and integrations
- Industry-specific packages: finance, healthcare, legal, manufacturing, customer service
In other words: less wow, more workflow.
The bottom line
Gen-AI isn’t failing—it’s being forced to grow up. The first wave proved it can generate text, code, and summaries. The next wave has to prove it can generate value: faster cycles, fewer mistakes, lower costs, better customer experiences.
The companies that get real ROI won’t be the ones that “use AI.” They’ll be the ones that change how work moves—and use AI to make that new system run better.
