What research tasks do we currently outsource or spend senior-leader time on that AI could accelerate?

AI research tools compress 10-20 hours of competitive analysis or regulatory review into 2-3 hours. The highest value is shifting senior time from research production to research interpretation.

How much do we currently spend on research — in time, consulting fees, or both?

Calculate the fully loaded cost — internal time plus consultants plus subscription databases. AI research tools typically deliver comparable quality at a fraction of the cost for routine research tasks.

If we could get a credible first draft of any research deliverable in two hours instead of two weeks, which deliverable would we start with?

The highest-value target is the research deliverable that currently blocks a decision. Compressing it from two weeks to two hours means the strategic decision it informs happens two weeks sooner.

Using AI in Your Work

Deep research with AI

By Mark Ziler · Last updated 2026-04-05

Deep research is a mode in tools like Claude and ChatGPT where the AI does not just answer from memory — it actively searches, reads multiple sources, synthesizes findings, and produces a structured research report. You can ask it to analyze a competitive landscape, summarize recent policy changes in your industry, or evaluate technology options against specific criteria. The output is often 10-20 pages of organized, cited analysis that would have taken a human analyst days. It is not perfect and needs verification, but as a first draft of research it compresses weeks of work into minutes.

Go deeper

Your board wants a competitive analysis of the three largest behavioral health platforms entering your regional market. Previously this meant hiring a consultant for $15K or assigning an analyst for three weeks. With deep research, you describe the competitive landscape you need analyzed, specify your criteria — pricing model, geographic coverage, payer relationships, technology stack, recent M&A activity — and get a 15-page structured analysis in about thirty minutes. It will not be perfect. Some data points will be outdated. Some sources will be secondary. But as a starting framework that you then validate and refine, it compresses the work from weeks to hours.

The trap most companies fall into is using deep research output as the final product instead of the first draft. The AI will present its findings with confident formatting that looks publication-ready. It is not. Treat it as a research assistant's first pass — check the key claims, verify the numbers that matter most, and layer in your own market knowledge that no AI has access to. The value is not in eliminating the research process. It is in starting at draft three instead of a blank page.

Questions to ask

What research task have we been postponing because it would take too long?
For our next strategic decision, could we use deep research to generate the initial analysis and then spend our time validating rather than building from scratch?
What internal knowledge would we need to layer on top of AI-generated research to make it actionable?