Why 90% of Companies See No ROI from AI – and What Will Change in 2026

According to recent studies by Deloitte and Gartner, 90 to 95% of companies see almost no measurable financial returns despite massive AI investments. Globally, 30 to 40 billion dollars have been invested in generative AI – with sobering results. The problem rarely lies in the technology itself.

AI as Advisor Instead of Executor

The most common mistake: companies deploy AI as a recommendation layer, not as an execution tool. AI can summarize, suggest, and analyze – but humans remain the bottlenecks that must translate AI insights into actions. Value is lost across fragmented systems, manual processes, and organizational silos.

The result: productivity improves at the task level, but company revenue stagnates. Only 20% of executives are satisfied with their AI investments.

What High-Performing Companies Do Differently in 2026

The most successful companies have fundamentally changed their approach:

• No replacement of legacy systems: Instead of expensive system overhauls, AI is orchestrated around existing infrastructure
• Redefining decision authority: Routine decisions with low risk are fully delegated to AI – complex decisions are escalated with context
• Autonomy as an operating model: AI agents handle execution, humans focus on orchestration and governance

Gartner forecasts: By 2028, 15% of all business decisions will be made autonomously – today that figure is practically zero.

The Governance Gap

With the rise of AI agents, a new risk is growing: only one in five companies has a mature governance framework for autonomous AI systems. Those deploying AI agents in production without defining clear oversight structures, escalation processes, and risk boundaries create uncontrollable dependencies.

Especially in regulated industries – finance, healthcare, public sector – this is not a theoretical danger but a concrete compliance risk.

What Swiss SMEs Can Do Concretely

The entry point doesn't have to start with a major project:

1. Identify a concrete use case – don't deploy AI in general, but solve a specific, measurable problem

2. Define success before the project starts – which KPI should improve in what timeframe?

3. Include existing systems – AI should be integrated into existing processes, not exist alongside them

4. Build governance in from the start – define responsibilities, escalation paths, and control mechanisms

Conclusion

AI delivers no ROI when treated as a tool rather than a change in the operating model. Companies that achieve real results in 2026 don't think in pilot projects – they think in processes, decisions, and measurable outcomes. At Business IT Partners, we guide you on this journey: from strategy development to concrete AI implementation. Get in touch.

Sources

• Deloitte: The State of AI in the Enterprise 2026 — deloitte.com
• Consulting Magazine: Why Enterprise AI Stalled and What Is Finally Changing in 2026 — consultingmag.com