The companies collecting a return from AI bought the same models everyone else did.
A majority of CEOs report neither higher revenues nor lower costs from AI in the last twelve months, while a minority reports both. Kerr Highland is retained for the difference: the firm finds what is holding a specific program's return, names it with evidence, and schedules its removal.
Where the firm practices
AI Operating Models
The pilot cleared its gate, the rollout thinned, and by the third quarterly review the benefits case had become a productivity narrative. The constraint behind that sequence lives in leadership, staffing, or process more often than in the models, and it shows in the delivery record. We name it with evidence, remove it, and leave the capability run by your own people.
Diligence & Value Creation
Every management presentation in the process now carries an AI slide. For funds and acquirers we measure the capability underneath it, what runs in production and at what error rate, and we write the finding to hold in the data room and before the investment committee. Post-close, the same examination sets the hundred-day plan.
Regulated & Scientific AI
Where a wrong answer is a reportable event, validation is laboratory work: failures characterized against defined denominators and documentation written for the inspection rather than the demonstration. The practice is led by a PhD pathologist whose method reduced production LLM hallucination from 22.1% to 1.1% (N=2,943).
Governed Agents
Autonomy is a credit decision, and most agent programs are extending it unsecured. The firm builds agent operations to a standard an auditor can sign: evidence for every action, the authority to halt at any time, and autonomy widened only against demonstrated performance, proven on a platform that carries SOC 2 Type 1 with 100% of controls passing.