AI is revolutionizing IT: it automates and puts an end to simple time-based billing. Service companies are – finally – refocusing on strategy and human judgment to sell results.
The next $1 trillion company won’t be a software company, but a technology services company. Behind this bold prediction lies a profound change in our industry. For more than thirty years, software has structured the digital economy. Today, theartificial intelligence reverses this model. It is no longer content with automating isolated tasks: it is redesigning the IT consulting value chain. The era of selling lines of code by the kilometer is coming to an end. Deciphering an inevitable revenge for service companies.
The Experience: The Mirage of Engineering and the Reality of the Factory at TJ
At the start of my engineering career, I idealized the world of technology consulting. In my mind, these firms embodied elite commandos. They solved the most complex technical and business equations. Then, the reality of the market imposed its law. Over the years, our sector has transformed into a huge ADR (Average Daily Rate) factory. The objective was no longer to deliver value, but to provide “billing fodder”. This drift has given rise to a new figure: the umbrella consultant. Many leaders today pay external service providers to validate their own instincts, or to provide themselves with an ideal culprit in the event of failure. Paying a firm just for reassurance is a silent admission of an internal trust problem.
The authority: Sequoia Capital and the advent of “Service as a Software”
Fortunately, the market is changing. Generative artificial intelligence acts as a revealer. The famous investment fund Sequoia Capital recently gave a name to this new dynamic: “Service as a Software”.
What is fundamentally changing? Companies no longer just buy a tool, they now demand a concrete result. The transition from means to result marks a major break. Technology now very clearly separates two worlds:
– Execution intelligence: Write code based on specifications, debug, test. Autonomous agents are taking care of this more and more quickly. The engineer becomes a manager of digital colleagues.
– Strategic judgment: Instinct, field experience, complex architecture, understanding of an economic model. The machine does not replace this human expertise, it augments it.
Expertise and Reliability: Pivoting towards the Business Partner Tech model
By delegating execution to AI, service stakeholders can transform their expertise into reproducible and scalable offers. Service companies can finally “platform” their approach. Faced with this observation, the model of tomorrow rejects the sale of man-time disconnected from the client’s business realities.
Common mistakes made by client companies:
– Buy resources rather than results: Focus your calls for tenders on the price of the day instead of the impact on the roadmap.
– Isolate service providers: Do not integrate consultants into overall strategic thinking.
The 3 best practices for a successful partnership:
– Require critical judgment: A good partner must know how to say “no” and shake up your technical certainties.
– Hybridize skills: Look for profiles capable of interacting with an API as well as with a financial director.
– Aim for co-responsibility: Assign tangible delivery and value creation objectives.
Understanding the IT market transition
The “real” service regains its letters of nobility. By entrusting execution to the machine, tech experts refocus on what really matters: judgment, informed advice and securing business trajectories. I invite you to assess the maturity of your technological partnerships: by questioning your internal teams about the real value provided by your service providers, beyond the simple product code.
