By: Natalie Johnson

As enterprises navigate rapid technological acceleration, the question of how work should evolve has taken on new urgency. Christophe Derdeyn, a global entrepreneur known for guiding organizations through complex digital transformations, has spent more than two decades building and scaling ventures while mentoring early-stage companies across Southeast Asia. He believes the rise of AI-driven automation will fundamentally reshape enterprise work by moving people toward higher-value responsibilities as new algorithmic approaches emerge beyond today’s LLMs.

Organizations that combine technological ambition with strong architectural foundations and thoughtful change management, he argues, will be the ones that define the next decade of business transformation. “When we went to the cloud, you supposedly were never going to need any infrastructure people anymore. Now the infrastructure people are still there, but the way they deal with things has shifted,” says Derdeyn.

The Next Decade Will Be Defined by Smarter Systems, Not Just Faster Ones

For Derdeyn, the consequential force shaping the future is the application of artificial intelligence across every layer of enterprise operations. Significant shifts are already underway. Companies are already automating research workflows, accelerating data processing pipelines, and streamlining customer support operations through AI-guided tools that reduce time spent on repetitive tasks. “A lot of the menial tasks which in the past were done by juniors or young people, research, data consolidation, data crunching, all of that is disappearing,” he says.

While coding will not vanish, parts of it will be substantially automated; however, widespread anxiety about job loss is misplaced. History offers a counterpoint. “When we went to the cloud, you supposedly were never going to need any infrastructure people anymore. Now the infrastructure people are still there, but the way they deal with things has shifted.” The same evolution will occur with AI. Roles will not disappear; they will change, and new types of work will emerge as automation frees people for higher-value activities.

Still, current large language models are approaching their limits. Companies are achieving improvements only by adding staggering amounts of data and computational power, which is not sustainable. Over the next decade, Derdeyn expects new algorithmic approaches to emerge and work in tandem with LLMs to unlock the next frontier of applications. “We are probably close to what they can do without exponentially increasing power consumption. In the next five to ten years, we will start seeing the first real-world applications of these different approaches.”

Where AI Is Succeeding Today

While many AI initiatives fail to meet expectations, Derdeyn sees clear areas of strong early traction. “90 to 95% of AI projects right now don’t meet the expected outcome, and that will change as we learn how to apply these better.” The most mature use cases fall into three buckets: research and data analysis, data capture and extraction, and customer interaction. These areas benefit from AI systems’ ability to process large datasets quickly, structure unstructured information, and generate consistent responses based on patterns.

The impact is already being felt across industries. “A fractional CMO mentioned that he used to have a team of about 70 people running marketing. Over the last one and a half years, his team has been reduced to about 20, and they do much more, much quicker.” Video editing, content production, and marketing automation have seen some of the biggest efficiency gains.

However, he warns of an emerging risk: AI feeding on its own output. With more than half of online content now generated by LLMs, the quality baseline may drop over time. “An LLM is basically the biggest common denominator of the data you push into it. Excellence will be hard to get, but a good average will typically be a decent outcome. The lower the bar of the content we push in, the lower the bar will become of the output.”

Three Practical Ways Businesses Can Build Resilience Through Innovation

Derdeyn’s approach to transformation begins with grounding initiatives in reality.

1. Conduct a thorough inventory of the current technology landscape. Map existing applications to business processes to identify pain points, estimate complexity and cost, and build a matrix that distinguishes between low-hanging fruit and longer-term strategic initiatives. Quick wins generate momentum, while more complex efforts support long-term strategy.
2. Create overarching objectives that unite efficiency with purpose. Drawing on his work with a global brewer, Derdeyn highlights how setting a target to use the least water in production delivered both environmental and financial benefits. A unifying objective rallies teams and shapes improvement priorities through a shared lens.
3. Invest early in change management and workforce readiness. Modernization ultimately changes how people work, and organizations that provide training, time, and incentives for teams to adapt stand a far greater chance of realizing the full value of new technologies.

The Overlooked Foundations of Successful Modernization

For all the attention given to advanced tools, Derdeyn believes the biggest barriers to modernization remain fundamental. Companies often rush to adopt new technologies without addressing legacy issues or designing a coherent architecture. “They see some kind of new application and go, this is going to solve everything,” he says, “but they don’t do a proper analysis on what needs to be in place before you can leverage a solution like this.”

Equally critical is the human side of transformation. New systems change how people work, yet organizations frequently underestimate the change management required. Without adequate time, training, and incentives, employees struggle to adopt new tools and initiatives become what Derdeyn calls “white elephants.”

Preparing for What Comes Next

As companies navigate the decade ahead, the future belongs to organizations that pair technological ambition with architectural rigor, thoughtful change management, and a commitment to continuous learning. For business leaders seeking to stay ahead, Derdeyn advises focusing less on noise and more on consistent, domain-specific learning. Whether through podcasts, newsletters, or vendor demonstrations, he believes leaders should stay close to developments in their own operational fields. “Make sure that in your particular domain, you follow whatever news source fits you well,” he says.

Follow Christophe Derdeyn on LinkedIn or visit his website.

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