Oskar Lehmann

The numbers need provenance. Without knowing the source, the timeframe, and the comparison baseline, I'm treating these as marketing claims rather than evidence. Finance audiences will push back hard on this. Include a methodology footnote or appendix slide.

The credible approach is to show one pilot result with clear ROI, rather than promising transformation across the board. That builds trust through proof, not hype. The current framing overpromises - dial back to 'we're testing' language.

From a finance controller standpoint, I need to see the business case upfront. The narrative arc should answer 'why should we invest in this' in the first three minutes. If I have to wait until slide 15 to understand the ROI, the presentation has already lost me and my leadership peers.

Number density is a trust test. If I see benchmarks and market sizes, I immediately wonder: what are the assumptions? What's the source? Can I trust this data? Without clear sourcing, numbers actually decrease credibility. I'd rather see fewer numbers with clear methodology than a dense data dump.

Finance and procurement leaders will be the skeptical segment. They've seen too many AI initiatives promised with big numbers and delivered with budget overruns. They need hard numbers tied to specific outcomes, not aspirational projections.

The most useful improvement: add a clear cost-benefit section with assumptions stated explicitly. Finance people will respect the transparency and it builds credibility rather than appearing to hide the investment side.

I need a capped pilot and one operational metric. Participation alone is not a business case.