Deloitte, ServiceNow warn enterprise AI falls on the human side
NEW YORK, UNITED STATES — Enterprise AI investment runs 93-to-7 in favor of technology over human development — and a Deloitte and ServiceNow panel at Fortune’s Brainstorm Tech argues this imbalance explains why most AI rollouts are underdelivering.
93 cents of every AI dollar goes to technology, not people
“The level of investment in the technology versus the human is woefully lopsided,” said China Widener, Vice Chair of Technology, Media, and Telecommunications at Deloitte.
Widener and Chris Bedi, Chief Customer Officer and Enterprise AI Advisor at ServiceNow, pointed to Amazon as a cautionary example: employees gamed a ‘tokenmaxxing’ system — maximizing AI processing consumption to inflate productivity scores — revealing how shallow KPI design converts AI adoption into metric manipulation rather than business transformation.
Approximately 90% of enterprise AI use cases are concentrated on internal cost reduction rather than revenue growth — a structural focus that limits AI’s total economic impact before companies have even addressed the human-side failures.
A trust problem becomes a culture problem
“If you have a trust problem, you’re going to have a culture problem,” said Widener. When employees view AI as a surveillance or replacement tool rather than an augmentation system, adoption stalls regardless of technology quality.
A PwC study cited in the session found that just 20% of companies capture nearly three-quarters of AI’s total economic value — a concentration that reflects organizational readiness, not access to better models.
Companies must move beyond time-saved metrics toward organizational key results aligned with business goals.
Centralized, embedded engineering teams — placed within business divisions rather than in isolated technology departments — are increasingly the recommended implementation structure.
‘Unlearning’ is cited as a core barrier: professionals with 20-year-old workflows resist AI adoption not out of ignorance but out of deeply embedded practice.
The gap between AI’s economic potential and current enterprise performance is not a technology problem — it is a change management problem, and the companies capturing disproportionate value are those treating AI adoption as organizational transformation, not software deployment.
For BPO providers embedded in client AI rollouts, the Deloitte and ServiceNow findings point to a service gap. The human side of enterprise AI — change management, upskilling, workflow redesign, and trust-building — is precisely the area that technology vendors and internal IT teams are underinvesting in.
Offshore BPO providers that can offer change enablement services alongside AI process implementation stand to capture the organizational transformation work that most enterprise AI programs are missing.
