Fortune's AIQ Summit: AI value needs redesigned work, not just tools

The summit's framing — experimentation to execution — reflects a shift the speakers described from tool distribution to organizational change. ServiceNow's Diana David pointed to a widening gap between 'pacesetters' and other firms on upskilling (57% versus 4%) and AI talent (68% versus 10%), while Paul Fipps argued the real gains come from rethinking processes rather than automating existing ones, citing Standard Chartered's 77% deflection of employee requests. Amy Webb added that Fortune 500 companies are 'pretty late to the party,' pouring capital into pilots without sufficient strategy or planning.

Workforce discussions extended beyond reskilling. HPE's Stacy Dillow warned against retrofitting AI into unchanged processes, Palo Alto Networks' Danielle Gonzalez said the company looks for curiosity and the ability to 'unlearn,' and Peloton's Francis Shanahan and Runway's Michelle Kwon flagged burnout and mistaking AI output volume for productivity. On governance, Bank of America's Hari Gopalkrishnan said rushing to AI when deterministic models suffice is a common mistake, and S&P Global's Sally Moore described data as 'the currency within AI.'

In physical and regulated settings, Honeywell's Suresh Venkatarayalu contrasted industrial customers' demand for 99.9999% reliability with frontier models that 'could be at 85%,' describing a near-term 'semi-autonomous world.' Ecolab's AJ Wijesinghe said using the best model for high-volume tasks sent 'tokenomics off the roof' and that the company cut token costs by roughly 70% to 80%. Booking's Ewout Steenbergen said customer-service costs are slightly down as bookings grow at a high-single-digit rate and roughly 9,000 engineers are getting about 30% more code into production, while cautioning that even hyperscalers spending hundreds of billions don't really know the ROI.