Databook today announced that Anton Stetsenko has joined the company as VP of AI Strategy and Deployment, where he will lead Databook's AI-native services organization — the forward-deployed engineers, AI strategists, and enablement leads who work alongside customer revenue teams to design, deploy, and operationalize AI go-to-market systems.
The appointment formalizes a shift in how Databook delivers value. Enterprises have spent two years buying AI capability and struggling to convert it into revenue. Even the strongest technology produces nothing until it is embedded in how sellers, managers, and operators actually work. Closing that gap requires a mutual commitment to process redesign, adoption, and outcome measurement, where vendors partner with customers instead of simply providing another login destination.
Stetsenko joins from Alvarez & Marsal, where he was a managing director leading end-to-end AI transformations for private equity sponsors and their portfolio companies — partnering directly with sponsors and CEOs to turn AI into a value creation lever with measurable impact. Before A&M he spent more than a decade at McKinsey & Company, most recently as an associate partner in New York, where he led the zero-to-one development and launch of McKinsey Contract AI. He holds an MBA from The Wharton School, where he graduated as a Palmer Scholar.
Under Stetsenko, Databook's services organization engages across the full arc of an enterprise relationship, beginning with a 90-day, risk-free proof of value:
Evaluation: Forward-deployed engineers embedded from the earliest weeks of an evaluation, building a working solution against the customer's real use case rather than promising a configuration after signature, baseline definition establishing what improvement means and decomposition of sales methodology into workflows AI can carry.
Co-design and deployment: Co-designed agentic workflows, built with the customer on Databook's platform, across use cases like territory scoring, account research and account planning, executive points of view, first-call and meeting preparation, value and discovery coaching, account prioritization and whitespace analysis, and renewal strategy. Integration with CRM, collaboration tools, and AI assistants plus governance design.
Adoption and enablement: Manager and seller enablement, change management, and redesign of the ways of working, Databook AI bootcamps that train GTM value architects inside the customer's organization.
Value realization: Measurement of results against the agreed baseline, reported against the milestones set at the outset and ongoing tuning of workflows and agents as motion, market, and priorities change.
"Enterprises are increasingly learning that buying an AI platform is not the same thing as getting value out of one," said Anand Shah, CEO and co-founder of Databook. "Value shows up when the technology is embedded in the way people already work, and that takes behavior change, not just software. Anton has run these transformations at scale."
"Companies don't need another consulting engagement that ends in a deck or another prototype that doesn't scale," said Stetsenko. "Real AI transformation happens when the intelligence, the workflows, and the people are all organized around what the customer is trying to achieve, not around the vendor's product."
About Databook
Databook delivers the industry's only true GTM Decision System, built on the Databook Customer Context Graph — a proprietary intelligence and AI deep reasoning framework that ensures go-to-market teams are consistently grounded in verified, actionable customer truth. Elite GTM teams from enterprises including Salesforce, Microsoft, Konica Minolta, Databricks, and Schneider Electric use Databook to build pipeline, advance deals, and scale consistency.
