A candid look at what blocks Agentic systems in real organizations 

As CTO for Data & AI at Sogeti, I often get asked: “If agentic systems are the future of AI, why aren’t we seeing them everywhere already?” 

It’s a fair question. The technology is maturing fast — systems that can reason, collaborate, and act autonomously is no longer science fiction. Yet, in real organizations, progress slows not because of the tech itself, but because of how organizations are structured to adopt it. 

Agentic systems—where autonomous agents negotiate, plan, collaborate and execute tasks in business workflows—represent a major leap forward in enterprise AI. The opportunity is real: smarter workflows, faster decisions, even entirely new business models.  

Yet most organizations remain stuck in experimentation. 74% of companies struggle to scale AI beyond pilots, and around 26% have the full set of capabilities required to generate tangible value. 
 
So what’s blocking progress? It’s not chiefly the algorithms—it’s the organizational readiness: 

• Silos of data and systems that inhibit agents from collaborating across functions. 

• Governance, trust and risk frameworks that are immature, making decision‑handover to AI feel unsafe. 

• Mindset and culture still built around “how do we build AI” not “what can agents now do for us.” 

• Time‑to‑market delays: many agentic initiatives stall at proof‑of‑concept (POC) or proof‑of‑value (POV) because each build starts from scratch, with governance, compliance and integration added-in later. Reports show that in many cases 88%+ of AI pilots never make it to production. 

• Change management gaps: employees and stakeholders often resist new workflows or AI-driven decision-making without structured adoption programs, training, and clear communication. 

• Skill and awareness gaps: limited understanding of AI capabilities and incorrect expectations lead to underutilization and slow adoption, as teams are unsure how to leverage agentic systems effectively. 
   

The opportunity then is clear: once organizations break through these blockers, they shift from “how do we build AI?” to “what can agents now do for us?” — and that’s when real value begins. 

  
In my experience, I’ve seen time and again that the difference between pilot and production isn’t just technology, it’s organizational readiness and deployment design. I’d recommend starting with data unification, lightweight governance, and trust-building pilots, iterating gradually to scale impact. 

However, this approach can be time-consuming, often taking months to align systems and culture for production-ready deployment. That’s where Sogeti’s Plug-and-Deploy AI Starter-packs accelerates the journey: pre-orchestrated, industry-tailored agents come ready with market knowledge, compliance controls, and tested workflows, enabling organizations to move from pilot to production from day one with minimal friction. 
 
For example: in the insurance industry, claims processing is a process rich with interactions—data validation, policy lookup, anomaly detection, and decision review. Instead of building each agent from scratch, our framework ships a collaborated set of agents pre‑trained with market and regulatory knowledge, orchestrated to work together, and tested for reasoning and flow.  

The steps to get to production then become: 

• connect organisational content and data systems 

• apply your ethics/policy layer 

• fine‑tune decision logic to your context. 
   

The benefit: reduced time to production, lower risk, and a platform that allows you to move from concept to value much more quickly. By embedding governance, orchestration and industry domain intelligence upfront, we help clients avoid the “pilot trap” and deploy with confidence. 

The impact of this approach is real. Clients who otherwise spend months in POC limbo are able to deploy agentic workflows within weeks.  

Agentic systems aren’t blocked by code—they’re unlocked by culture. The technology is ready; what’s less ready is how organisations are structured, governed and enabled to let AI act. If you’re embarking on this journey, start with deployment in mind, build trust early, and ask not just “what can we build?” but “what will these agents now do for us?”  

The future isn’t about smarter agents—it’s about smarter organisations.