MIT Technology Review Insights has published a report on agentic AI in partnership with Microsoft. The report is titled “Agent confidence on the technical frontier.” It ranks 101 tasks across AI, data and cloud workflows. Each rank reflects how much practitioners trust agents with the task.
The research team surveyed 300 technology executives, team leaders and contributors in February and March 2026. The respondents span 12 industries, and their organizations range from startups to firms that reported upward of $10 billion in annual revenue. Every score runs on a zero to 100 scale. Practitioners rated only the tasks within their own domain.
Here are the key takeaways from the report.
1. Automated report generation tops the confidence index
Automated generation of business reports and their distribution to stakeholders scored 83.5, the highest confidence rating the survey reported. Technology experts trust agents with this task the most. Boilerplate code generation for new software features follows closely at 82.5. Both tasks are tedious for developers and easy to verify, which explains why teams are happy to hand them over.
2. Agents earn trust through scoped and measurable work
The pattern across the top of the index is consistent, with straightforward and low-risk tasks drawing the highest confidence. The report notes that trust runs high in boilerplate code generation because teams can measure merge rates into the main code base. That single metric tells them whether the generated code meets the quality bar.
3. Data workflows are the breakthrough domain
The index reported a score of 82 for data quality monitoring, while real-time data stream monitoring and automated data profiling both land at 80.5. Tech teams trust agents most where structure provides a reliable foundation for decisions. Domain experts closest to the point of data generation can supply the context that allows agents to act and deliver trusted outcomes.
4. Business context is a bigger blocker than capability
Where agent readiness drops, the report attributes it to a lack of business context supplied to agentic systems rather than to raw model capability. Even listing the top 10 customers by revenue requires context. The agent needs to know which customer column to use, how the company calculates revenue and whether the calendar is fiscal or calendar year. A new data analyst would need the same briefing.
5. Complex multi-step workflows sit at the bottom
Respondents rated service mesh configuration and troubleshooting at 37.5, the lowest score in the index. Disaster recovery testing scored 43, according to the index, and database migration planning 44.5. These tasks touch live infrastructure, coordinate long workflows and depend on organizational knowledge that agents are only beginning to accumulate.
6. Keeping humans in the loop is the leading mitigation
When asked how they address their concerns, 59% of respondents told the researchers they plan to keep humans in the loop. Another 53% are monitoring agent activity closely and tracing decision inputs. For high-stakes or irreversible scenarios, the survey participants expect humans to make the final call while agents recommend.
7. Accountability and hallucinations are the two main concerns
Respondents ranked accountability for decisions made by agents as the top concern at 48%. The potential for inaccurate results and hallucinations follows close behind at 47%, the report noted. Unpredictability of results comes third on the list. Both concerns point to the same gap between what agents can execute and what teams can explain after the fact.
8. The worry differs by role
The survey found executives focused on accountability at 54%, since they answer when agent decisions go wrong. Individual contributors, the survey reported, worry most about hallucinations at 56% and about losing expertise in their craft. A smaller group of contributors fears being replaced outright. The report argues organizations must respond by investing in junior talent rather than cutting it.
9. Streamlining processes leads the agent agenda
51% of respondents cite streamlining processes as the biggest opportunity agents offer for everyday work. Improving performance and reducing repetitive tasks follow. Executives lean toward enabling scale, while team leads prioritize streamlining their teams’ processes.
10. Technology experts expect agents to advance their careers
For cloud workflows, 96% of respondents reported they are confident that using agents for system reliability will help their career prospects. AI workflow respondents feel the same about evaluation and quality assurance at 92%. The report makes a convincing case that confidence, not capability, is the real currency of agent adoption. As experience deepens and business environments mature, expect the confidence gap in areas such as disaster recovery to close.
