CIO Insights 1Q2026

Equities markets have become increasingly concerned about the disruptive effect that AI, especially in its agentic form, will have on companies in industries ranging from Software as a Service (SaaS) and miscellaneous professional services (e.g., accounting, consulting, marketing, education, customer relationship management or freight logistics) all the way to financials such as fintechs, rating agencies, credit card processors and traditional players in banking and asset management. There cannot be a broad-brushed assessment of the impact. Every firm and every analyst looking at them will have to evaluate in frank terms how sensitive a particular business model is and how it should be adapted accordingly. This uncertainty is of great interest to us. Especially among select professional services firms that enjoy entrenched competitive positions and high client loyalty, we can see the market potentially overreacting.

The first order of concern, however, is to evaluate our own cooking: will AI make us obsolete? Ultimately, of course, it is our clients who are the judges as to how relevant our offering is to them within the context of their overall asset allocation programs. From our vantage point we are convinced that the broad commercialization of AI presents a net positive for our business, for two crucial reasons. The first is related to what AI can do for us and the second how it helps to further differentiate our contrarian approach versus other, more conventional strategies.

First, let’s shed light on how we manage to productively deploy AI. On one level, it makes several aspects of our day-to-day business support operations more efficient. Many data processing tasks and analytics so far have been managed with separate tools on varied platforms. Agentic AI now facilitates and enhances their interoperability, which leads to better overall information outcomes while greatly reducing the need for manual input. On another level, our investment research process likewise becomes more efficient. Relevant but basic due diligence information on business metrics, competitive analysis, strengths and weaknesses, threats and opportunities and macroeconomic sensitivities are much more rapidly distilled out in an AI world than before. Both factors free up precious time and resources that can be reallocated to our very business reason: weighing the strategic merits and prospects of individual firms, putting a value on them, managing the portfolios and interacting with clients.

Now, let’s look at AI’s shortcomings and how they help us in unintended ways to further differentiate our product offering. In plain terms, AI cannot supplant the human judgment skills necessary to evaluate whether we want to buy and then own a stock over a long period of time. Specifically, AI lacks the ability to help us develop a sound investment thesis around a divergent perspective on a business and hence its financial trajectory going forward, versus that implied by the market. To recall, we are dedicated contrarian investors looking for the counterintuitive, the misunderstood, the quirky, the obscure. A big part in a contrarian investor’s playbook is to be on the lookout for unexpected improvements in business conditions and eventual recovery form previously observed negative earnings trends. Our experience so far has been that AI, at least in the form of so-called large language models (LLMs), is built on an extrapolative, linear “reasoning” process. It is prone to develop predictive conclusions that fall mostly in line with what a conventional, consensus-based investment analysis would indicate. It follows that AI has difficulty in dealing with nonlinear systems, where an economic pattern may start to deviate from recently observed norms (as would be the case, for instance, in corporate turnarounds or at the nadir of business cycles).

Concurrently, we surmise that the consequences of how AI works and its ubiquitous availability to the investment management industry renders future investment decisions even more uniform. If everybody uses the same assumptions and input feeding their AI-driven algorithms, even fewer off-consensus views will be left to impact prices. This in turn will likely lead to more instances where individual companies may be significantly mispriced by the market, presenting new opportunities for us.

Thus, AI should benefit our business, both purposely and inadvertently. Most importantly, we will view the future as being AI-enabled, as opposed to AI-dictated. This means that we are determined to use AI in our favor and exploit its pros and cons, without becoming enslaved by it.

Sincerely,

Gregor Trachsel
Chief Investment Officer SG Value Partners AG