The rise of generative AI has sparked questions, expectations, and sometimes even unease within many organizations. Future Workforce observes that while companies recognize AI’s potential, they are often still searching for a structured approach. In a conversation with Edwin Provoost of Future Workforce, it becomes clear how the company helps organizations advance on their journey toward AI maturity.
According to Provoost, discussions rarely begin with a concrete request like “we want generative AI.” The demand in the market is less advanced than many vendors suggest. “You see plenty of posts on LinkedIn about how easy AI applications are, but within organizations, a clear vision often lacks. Employees experiment, but there’s no cohesion or structure,” he explains.
Awareness, however, is growing. Organizations want to understand what AI can bring them, though the focus often remains on productivity. Provoost cautions that seeing AI merely as a time-saver means missing larger opportunities. “It’s about value creation: better marketing, faster customer interactions, smarter sales.”
AI Agents and the Combination of Technologies
Future Workforce does not view AI as a stand-alone tool, but as part of a broader technological mix in which automation, machine learning, and generative AI converge. This convergence enables what is known as Agentic AI—automated workflows that can independently perform tasks based on prompts, data insights, and learning capabilities.
“AI agents are changing the work of the classic RPA developer,” says Provoost. “No more scripting from static process design documents, but smart workflows (BPMN) that understand what needs to happen.” This makes automation less vulnerable to change and easier to apply, even for lower-volume processes.
Agentic AI also brings more autonomy, requires less maintenance, and increases process flexibility. It makes it possible to automate processes once considered too small or complex—such as ESG reporting or dynamic customer interactions.
The Path to Maturity
The market is not there yet. Many organizations struggle with legacy systems, messy data, or limited change capacity. “The technology exists,” says Provoost, “but organizations are not always able to keep up. Larger companies especially struggle with this.”
Future Workforce therefore focuses on structured guidance. This begins with knowledge transfer at the executive level (“In the land of the blind, the one-eyed man is king”) and progresses through workshops and discovery sessions to concrete implementations. The approach uses fixed frameworks and scenarios that link AI, automation, and business objectives.
“Appointing a Chief AI Officer and thinking you’re done is a recipe for disappointment,” says Provoost. “You first need to understand what you want to achieve—fewer errors, higher revenue, more efficient processes. From those goals, you determine which technologies fit.”
The Role of IT and the Changing Reality
The IT department plays a key role, but can also be a bottleneck. Fear of losing control can lead to hesitation. Provoost argues for close collaboration between business and IT. Separate AI working groups detached from existing centers of excellence are not the solution, he says.
The role of Future Workforce is also evolving—from traditional implementation partner to advisor and guide. “We help organizations become mature enough to manage automation themselves. We, too, must continuously develop our services.”
AI as an Assistant—with Room for Humans
Although generative AI can now operate with increasing autonomy, the human role remains essential. AI supports insight, structuring, and decision-making, but interpretation and action remain human tasks. At the same time, this autonomy reduces the need for manual work.
“You create time,” says Provoost, “but you must use that time wisely. Without redesigning tasks and developing new skills, the added value will not materialize. HR and strategic management must address this, especially in larger organizations.”
Adoption rates differ as well: startups and scale-ups tend to have technology in their DNA, allowing them to adapt faster. Larger, more rigid organizations face greater challenges. Future Workforce also assists with organizational repositioning—how to use freed-up time, and whether employees have the skills to take on new responsibilities.
Quick Wins and Maturity
For less mature organizations, it is advisable to start with quick wins. Small, manageable AI applications help build confidence and experience. From there, more complex initiatives can follow. “We see companies achieving real value only once the fundamentals are in place: cloud-based infrastructure, solid data management, and a clear business vision,” Provoost notes.
A good example is the use of AI for ESG reporting. Generative AI can combine and interpret various data sources, enabling faster and more complete reporting. Where RPA alone fell short, the combination with AI proves effective.
From Potential to Practice
The shift from AI potential to concrete application is increasingly visible in customer-facing processes such as customer service, where the greatest time savings can be achieved. “You can generate questions, formulate answers, and even execute transactions—all within one AI-driven flow,” says Provoost.
This development aligns with broader technological trends. Speech recognition and text-to-action have become mainstream. Organizations must ask themselves: will we limit AI or leverage it? And if they choose the latter, it must be properly organized.
AI Requires a Roadmap
Provoost’s message is clear: don’t jump into AI blindly—work with a roadmap. AI is a journey that requires structure, vision, and organization-wide involvement. Only then can companies harness AI as a driver of true value creation. “As Gartner put it well: ‘AI is a journey, so create a map.’ That map determines whether you use AI as a hype or as a strategic instrument.”
Future WorkForce is a founding partner of AI & Automation Day 2025.
See also
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