BearingPoint study reveals most organisations are not fully leveraging AI's potential in operating model redesigns

A new report from BearingPoint highlights that despite widespread AI adoption, only a minority of organisations have realigned their operating models to unlock the full value of emerging technologies, pointing to a significant readiness gap.

Management and technology consultancy BearingPoint has published a study claiming that while many organisations are advancing AI initiatives, only a small minority have reshaped their operating models to capture the technology’s f...

According to the announcement, the report, based on a quantitative survey of nearly 400 C‑level executives across Europe and follow-up qualitative interviews, finds that new technology and artificial intelligence are now the single strongest strategic drivers of operating model redesign. The firm said 69% of respondents cited AI or new technology as a top driver, while evolving customer expectations were named by roughly half. Yet only 4% of surveyed organisations described their target operating models as fully aligned to support strategic goals, a gap attributed to fragmented governance, unclear accountability, outdated processes and weak business–IT integration.

“Organizations can no longer rely on static models built for predictable environments,” Rémy Sergent, Partner at BearingPoint, is quoted as saying in the announcement, arguing that future‑ready companies are redesigning how work gets done so teams can “move faster, collaborate more effectively, and use AI in ways that enhance both decision‑making and customer value.”

The study sets out five imperatives for next‑generation operating models: connect corporate strategy with the target operating model; focus on leadership alignment and cultural readiness; clarify roles, decision rights and performance systems; digitalise and streamline processes; and build data and technology foundations that activate AI across the enterprise. The firm framed successful organisations as those that adopt a continuous evolution mindset, treating operating models as modular systems that flex with market change.

While the findings present AI as the primary catalyst for change, the report also highlights persistent people and capability challenges. The announcement says talent development, data literacy and cross‑functional teaming remain slow to move, limiting transformation outcomes despite investment and strategic intent. The firm noted that organisations with more mature operating models reported clearer decision rights, stronger governance and faster implementation cycles.

The study’s conclusions are offered against a backdrop of business expansion and new product development from the consultancy itself. The firm said it exceeded a billion euros in full‑year revenue in the previous year and has been increasing partner ranks and headcount to support global growth. It has also developed an AI‑powered platform for enterprise transformation that it reports has produced significant productivity gains in tested SAP programmes, the announcement adds, evidence, the company suggests, that consultancies are scaling proprietary tools to accelerate client transformations.

Observers advising on large‑scale change often caution that vendor‑led case studies and internal metrics should be weighed alongside independent measures of business impact and workforce outcomes. The announcement acknowledges this tension implicitly by emphasising governance, leadership alignment and cultural change as prerequisites for turning AI potential into measurable results, rather than treating technology as a standalone fix.

Tobias Liebscher, Partner at BearingPoint, is quoted as saying: “Technology is only one part of the transformation story,” and urging organisations to align structure, processes, people and culture so AI and data deliver measurable results. The company said those that delay face the risk of falling behind as speed, data‑centricity and cross‑functional collaboration become decisive competitive factors.

The report frames a stark readiness gap: while a large majority of leaders self‑assess as prepared for future demands, only a sliver say their operating models are truly future‑ready. The firm’s blueprint and its own growth and product launches are positioned as part of a market response to that gap, advocating disciplined, enterprise‑wide redesigns to convert AI investment into scaled business impact.

Source: Noah Wire Services