How to scale AI: From great grassroots momentum to true bottom-line impact

Industry insights

How to scale AI: From great grassroots momentum to true bottom-line impact

By Christiane Jauch

27.10.2026 – 20 min read

Research at a glance

Up to 3–5%

P&L impact reported by companies interviewed

95%

less process time in a reimagined end-to-end accounting workflow

70%

of selected operational workflows automated, with 2X output and 80% fewer production incidents

From AI momentum to measurable business impact

Leading adopters are already turning AI into measurable revenue, cost, and capacity gains. Drawing on executive interviews conducted in 2026, this paper sets out what they do differently across three capabilities: Ambition, Governance, and Scaling.

Six imperatives to help you scale AI

Ambition

Anchor AI in a clear business imperative
Concentrate investment on a few key workflows

Governance

Set up central governance and assign business accountability
Assemble a secure, interoperable backbone

Scaling

Reinvent workflows, roles, and routines with the advanced adopters
Accelerate adoption through a combination of pull and push

What you’ll learn

How to put the P&L in charge of AI transformation
How to prioritize workflows and fund initiatives based on demonstrated value
How to combine central AI governance with business-led delivery
How to build a secure backbone that can adapt as models and providers change
How to involve frontline teams in workflow redesign and adoption
How companies at different starting points can build on existing momentum

Download our whitepaper now to explore the six imperatives for scaling AI, from setting ambition and governance to redesigning workflows and accelerating adoption.