Companies no longer seek to “add AI to everything,” but instead demand solid infrastructures and results that positively impact the financial bottom line—outcomes that justify the investment, in both time and money, required to integrate an AI solution into production processes.
At Baufest, we believe these are the five trends that will shape the strategic agenda of 2026:
1. Expectations around AI are changing: focus on ROI and governance
The period of overwhelming enthusiasm for AI is over. In 2026, delivering real and measurable results will be essential, forcing technology and security leaders to recalibrate their investments under stricter financial scrutiny. In fact, estimates suggest that companies will delay up to 25% of their planned AI spending to 2027 because the expected returns on AI investments have not materialized as anticipated. Governance will also be critical: a quarter of CIOs are expected to be called in to “rescue” AI projects led by business units that lacked proper quality management. Success now depends on robust governance and on the ability to analyze the data generated by AI tools to understand their effectiveness so far, helping avoid business-driven strategic failures.
2. Software development powered by AI
We are witnessing an ongoing evolution in software development, where AI is moving from assisting developers with specific tasks to fully taking on delegated work through autonomous agents. This shift enables hybrid teams in the short term (human + AI agent), where humans define intention and design while agents execute and optimize. It also projects us toward a near future in which AI agents collaborate with each other, coordinated and governed from a common platform—such as GitHub—transforming the human role from writing code to orchestrating business outcomes.
3. Cybersecurity: AI secure lifecycle
Cybersecurity in 2026 leverages AI to anticipate and neutralize attacks before they occur (preemptive). With projections indicating that documented vulnerabilities will exceed one million annually by 2030, companies are adopting AI Security Platforms (AISPs) to protect both third-party services and custom applications from emerging AI-driven attacks such as prompt injection and data leakage. Eighty percent of unauthorized AI transactions will stem from internal policy violations rather than external attacks. Integrating security from the beginning of the software development lifecycle—and at every level—is now essential to ensure robust products.
4. AI Ready SEO: visibility in the era of chatbots
The way users find information has changed. Traditional search now coexists with generative AI models that synthesize answers directly. Brands must optimize the way they appear online to become the preferred option for AI-driven platforms. This requires an approach that combines authority, strategic content, and technical-semantic optimization to stand out in new search patterns.
5. Cognitive hybrid infrastructure
To support increasingly complex AI models and multi-agent systems, organizations are migrating toward hybrid infrastructures and AI supercomputing. It is expected that 40% of companies will adopt hybrid computing architectures by 2028. Additionally, so-called neoclouds (such as CoreWeave or Lambda) are challenging the dominance of major cloud providers by offering high-performance infrastructure specifically optimized for GPUs and sovereign AI solutions.
In summary, 2026 will be the year in which AI stops being an accessory and becomes the engine of a productive, secure, and efficient organization. But to achieve this, companies will need to take a proactive role and closely follow the implementation of these technologies to ensure their success.
