- AI moves from hype to backbone: Agentic AI emerges as the next frontier for enterprise resilience
- Global study shows only 8% of organizations are scaling AI initiatives as planned
- 7% of organizations have embedded agentic AI architectures enterprise-wide
- Blueprint offers C-suite leaders a roadmap to accelerate transformation and secure competitive advantage
Management and technology consultancy BearingPoint has released a new thought leadership report, “Resilient by design: How Agentic AI is reinventing organizations.” The study reveals that 7% of organizations have fully integrated AI across the organization, underscoring an urgent need for C-suite leaders to move beyond pilots and embed AI into the core of their operating models and prepare for the next frontier: agentic AI.
Drawing on a global survey of 1,010 senior executives across industries and geographies, as well as BearingPoint’s real-world client experience, the report identifies the structural, cultural, and governance changes required to operationalize agentic AI at scale. It provides a roadmap for organizations to evolve into resilient, adaptive enterprises capable of thriving in a world where AI agents act, make decisions, and collaborate in real time.
“AI is the new backbone of competitiveness,” said Frederic Gigant, Partner and Global Leader Customer & Growth at BearingPoint. “Generative AI may have grabbed all the headlines, but the real inflection point is agentic AI. Companies that rethink and rebuild target operating models around agentic architectures will not only gain efficiency but also set the pace of innovation and resilience for their industries.”
Key findings from the study
The study reveals a widening gap between AI leaders and laggards, as organizations grapple with scaling challenges, workforce mismatches, and the slow adoption of next-generation agentic AI architectures.
Maturity gap: 26% of organizations have moved beyond pilots to scale AI across core operations, while 20% remain hesitant and risk falling behind. Key obstacles include regulation (47%), legacy infrastructure (35%), and resistance to change (26%).
Workforce dual challenge: 92% report up to 20% workforce overcapacity in legacy roles, while 94% face acute shortages of over 30% of AI-critical skills. Yet fewer than half (46%) embed workforce planning into their AI transformation.
Scaling shortfall: Scaling AI-driven projects is still an issue. Today only 8% of executives report that their AI initiatives have been fully scaled and are meeting initial expectations.
Agentic AI architectures1: More than half of organizations (54%) remain in the earliest phases of agentic AI architecture, with only 7% reporting enterprise-wide scaling. While 17% expect full adoption within 1–2 years, the majority (71%) foresee scaling in 3–7 years—highlighting the widening risk for those stuck in pilot programs.
Strategic implications for leaders
While efficiency remains the most immediate benefit of scaling AI, the research highlights a broader competitive edge for those willing to redesign their operating models around agentic systems. Organizations that commit early are not just automating tasks; they are creating a new class of AI-empowered workflows and decision-making structures.
The workforce findings point to a dual challenge: managing overcapacity in legacy roles while simultaneously addressing shortages in AI-critical talent. Leaders must invest in reskilling and workforce planning at the same pace as they scale AI technology. Without this alignment, even ambitious AI strategies will stall.
Governance also emerges as a decisive factor. The study shows that organizations succeeding with agentic AI are those that embed accountability and traceability into their systems from the start. Explainability and auditability are prerequisites for scaling responsibly.
From pilots to platforms: blueprint for transformation
The study emphasizes that AI pilots and proofs of concept are no longer sufficient; instead, a more comprehensive approach is required. To achieve scale and impact, organizations must:
- Transform enterprise systems and governance by embedding AI agents into the core, not as an add-on.
- Redesign operating models end-to-end with agent-executable processes, hybrid human-agent teams, and adaptive workflows.
- Develop scalable governance frameworks that extend decision rights to digital agents while ensuring oversight and compliance.
- Synchronize AI transformation with workforce evolution, ensuring roles, skills, and culture adapt at the same pace through a single, integrated roadmap.
These elements together form a blueprint for scaling AI transformation across the enterprise. The companies that move fastest to integrate agentic AI into their operating core will create structural advantages that competitors will find difficult to replicate. Those who remain in experimental mode risk not only missing short-term efficiencies but also losing their market position in sectors that are rapidly being reshaped and even reinvented.
“The winners of the agentic age will be those who act with urgency,” emphasizes Frederic Gigant. “Every month lost is a month in which competitors advance. The maturity gap is widening, and organizations that wait will not only fall behind in efficiency but may forfeit their ability to lead in innovation, resilience, and customer trust.”
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