AI does not eliminate IT services. It redefines who is valuable in an M&A
Reading time
8 minutes
Date
Aug 20, 2026
Author
Rafael Frugis — Sócio, IT & Professional Services, igc Partners
For this reason, the question of whether artificial intelligence is a risk or an opportunity for technology companies does not have a single answer. The impact will depend on the type of service offered, the complexity of the deliverables, the relationship built with clients and, above all, the ability to turn technology into concrete results, but one thing is certain: every company must dig deeper into the topic and use Artificial Intelligence to its advantage.
Those who sell only a tool, a piece of software or an easily replicable capability may see their business model come under pressure. Those who combine technical depth, business knowledge, proximity to the client and real implementation capacity may come out of this movement even stronger.
This difference is already beginning to appear in how buyers and investors analyze companies in the sector.
In software companies and technology products, artificial intelligence can significantly reduce the time and cost of developing new solutions. Features that once required large teams and long build cycles can be developed faster.
This tends to lower some barriers to entry and allow the emergence of new competitors. It can also make it harder to sustain high prices when a significant part of the solution can be reproduced or incorporated into larger platforms.
It does not mean that all software companies will lose value. Companies with proprietary data, significant distribution, strong integration with clients' processes and products that are critical to operations will continue to occupy strategic positions. However, poorly differentiated products or those based only on features may face more intense competition.
In the technology services segment, the analysis is different.
The technology used in execution is only part of the value proposition. In many projects, what really differentiates a company is its ability to understand the client's problem, design the appropriate solution, integrate it into existing systems and lead the transformation within the operation.
These elements are harder to replicate than an isolated tool. They depend on trust, a track record of execution, qualified teams and accumulated knowledge about the critical processes of each industry.
This does not mean that all service companies will be protected from the disruption caused by artificial intelligence.
Highly standardized, repetitive services that depend exclusively on staffing tend to feel greater pressure. If artificial intelligence makes it possible to perform an activity in less time or with a smaller team, the client naturally begins to question contracting models based only on the number of hours.
One way to understand this transformation is to separate intelligence from judgment. A large part of programming work can be described as intelligence: it involves rules that can be extremely complex, but that remain rules and, precisely for this reason, can be learned, accelerated and, in some cases, replicated by artificial intelligence.
The work of IT Services companies, however, is not limited to this layer. In the higher value-added activities, it combines intelligence with judgment: the ability to make decisions in situations where there is no objective answer, assess trade-offs, interpret different variables and define the best path from each client's specific context.
This judgment is not easily codifiable. It is built over years of practice, over experience accumulated across different projects and, above all, over deep knowledge of the client's business, processes and priorities.
That is why services that involve complex decisions, integration between different systems, sector knowledge and responsibility for results tend to be more defensible. Artificial intelligence can accelerate execution and expand the technical capacity of teams, but it is still necessary to decide which problem should be solved, which risks should be considered and how the technology should be applied to generate real impact on the business.
On the other hand, when a company essentially sells effort, performs easily replicable activities and does not have a clear specialization, the risk of standardization increases. The efficiency provided by technology can be absorbed by the client, while the supplier faces greater pressure on prices and margins.
Artificial intelligence, therefore, does not eliminate the work of IT Services companies. It changes where the value of that work lies: less in the execution of tasks that can be turned into rules and more in the ability to apply knowledge, context and judgment to solve complex problems.
In this new model, the division of labor also changes. The winning companies will be those that discuss strategy with the client, understanding the business problem, the priorities and the risks involved, and use artificial intelligence to accelerate and scale execution. The strategic conversation remains human; delivery gains speed and precision with technology.
Instead of using technology only to reduce costs, these companies can apply it to analyze more information, anticipate problems, accelerate decisions and offer more complete solutions. Efficiency ceases to be only an internal advantage and becomes part of the value delivered to the client.
This transformation also requires a commercial change.
Models based exclusively on hours worked tend to lose relevance in the face of proposals tied to efficiency, productivity, automation and impact on the business. The more clearly a company can demonstrate the result produced, the smaller the direct comparison on price tends to be.
In this context, artificial intelligence ceases to be a competitor and starts to function as a lever. It increases the team's capacity, expands the number of problems that can be solved and allows professionals to focus on more complex activities.
The winners probably will not be those who try to compete against the technology, but those who manage to use it better in the client's favor.
The acquisition of BITKA Analytics by BIP, in which igc acted as BITKA's exclusive advisor, illustrates this movement well.
Founded in 2020, BITKA brought together more than 140 data specialists and developed solutions that combined artificial intelligence, optimization, software engineering and machine learning. The company had also built strong specialization in the mining sector, applying predictive and prescriptive modeling and generative artificial intelligence to complex problems of large companies.
The strategic relevance of the asset was not only in the use of artificial intelligence. It was in the combination of technology, specialized talent, sector knowledge and practical application capacity.
For BIP, a global management and digital transformation consultancy, the transaction expanded its international network of specialists, strengthened its end-to-end capabilities and accelerated its expansion in Latin America, especially in a strategic sector such as mining. The buyer highlighted precisely the talent, the technical expertise and the sector experience of BITKA as central factors in the acquisition.
The case shows that artificial intelligence does not necessarily reduce the value of service companies. When embedded in a differentiated value proposition, it can increase the attractiveness of the asset.
The buyer is not acquiring only a technology. It is incorporating a team capable of using it, a track record of projects, a position in a given industry and relationships that would take years to build organically.
From an M&A standpoint, buyers and investors tend to look more closely at the quality of the capabilities behind the growth.
A company can adopt artificial intelligence quickly. Building qualified teams, sector knowledge and credibility to operate in critical processes takes much longer.
That is why companies that combine technical depth, close relationships with clients, integration capacity and a proven track record of execution tend to occupy a more defensible position.
The ability to turn knowledge into a replicable methodology also gains importance. The less the service depends on isolated initiatives and the more the company manages to structure its own processes, tools and models, the greater its ability to grow without losing quality tends to be.
Industry specialization is another relevant element. Deeply knowing sectors such as financial services, healthcare, retail, mining or agribusiness allows the company to understand not only the technology, but also the risks, the processes and the decisions that determine the client's result.
This knowledge reduces implementation time and makes the commercial relationship more strategic. Instead of being only a technology supplier, the company comes to play the role of a transformation partner.
Artificial intelligence should also increase the distance between differentiated companies and poorly protected businesses.
Buyers will continue to be interested in the sector, but they should be increasingly discerning. Revenue growth, on its own, may not be enough. It will be necessary to understand how much of that growth is associated with services that can be automated, how relevant the company is to its clients and how the company intends to protect its position in the coming years.
Companies that demonstrate a clear strategy for artificial intelligence, accompanied by concrete cases of application and impact, will have a more consistent narrative. Those that use the topic only as rhetoric may face questioning during due diligence.
The market tends to reward assets that use technology to expand results, and not only to reproduce existing services at a lower cost.
Even in an environment of greater selectivity, differentiated companies remain capable of attracting strategic buyers and valuations that recognize their position. Technology can change the tools used, but it does not eliminate the importance of knowledge, trust and execution capacity.
Artificial intelligence should not be treated only as a threat to be avoided. For technology services companies, it represents an opportunity to review the business model, raise productivity and build more relevant offerings.
The central question is not whether artificial intelligence will replace certain services. It is whether the company will manage to use it to deliver more value than its competitors.
Companies that continue selling only capacity may face pressure. Those that manage to combine efficiency, automation, applied intelligence, strategy and deep knowledge of the client will be able to strengthen their position.
In the next consolidation cycle, this difference will be decisive. Buyers will not look only for companies that use artificial intelligence. They will look for organizations capable of turning that technology into real, recurring results that are hard to replicate.
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