Technology companies are beginning to make a strategic shift in the way they invest in innovation. As highlighted in the new Unisys global reportthe next era of enterprise technology will be characterized by a clear preference towards business applications smaller, specialized and of higher quality, compared to large projects aimed solely at reducing costs. The document, based on the opinions of experts and company executives, identifies ten key trends that explain this paradigm shift and its impact on productivity, cybersecurity and talent management.
The main conclusion that can be drawn from the multinational’s report is that artificial intelligence (AI) is moving from promises to measurable results. Organizations are beginning to integrate more content developments, adjusted to specific tasks and integrated into their current processes, which guarantees greater agility, a clearer return on investment and a less risky implementation. As Mike Thomson, CEO of Unisys, has pointed out, “in 2026 we will see more functional deployments of AI and there will be a clear commitment to quality by companies to the detriment of cost reduction and the emergence of business applications ROI-oriented.
Packaged business applications
Unisys research highlights that, after years of experimental projects in Artificial Intelligence, organizations and more specifically IT departments, are consolidating a small set of repeatable solutions, including internal and external chatbots, virtual assistants or intelligent programming agents. These tools are becoming business applications packaged, measurable and rapidly adopted, which is changing the way companies evaluate technological profitability. In this context, size matters less than impact because what is fundamentally sought is precision, specialization and immediate results.
Another important change with respect to previous years is the abandonment of large generalist models. Companies are training AI models with smaller, cleaner, and industry-specific data sets, resulting in more accurate, efficient, and reliable results. This trend reinforces the idea that technological strategies with less complexity do not mean less value, but rather greater control of the innovation cycle and better risk management.
AI and security: containment rather than prevention
The impact of AI is not limited to operational efficiency or decision making. It also redefines defense against cybercrime. The Unisys report notes that both attackers and security managers are using AI to automate their tactics: from generating malicious content (such as phishing or voice spoofing) to strengthening anomaly detection and automated response. The goal is no longer to avoid a breach at all costs, but to achieve rapid recovery and demonstrable resilience to regulators and customers.
Furthermore, emerging themes such as post-quantum cryptographydigital sovereignty or the end of “cloud-only” approaches take center stage. In all cases, the focus is on making smarter and more sustainable decisions about where to host, process and protect data. Companies that understand these dynamics early will have an advantage over those that persist in models focused solely on cost reduction.
As the report shows, large corporations are learning that the true value of business applications It lies not in scale or immediate cost savings, but in its ability to deliver tangible, resilient results that are strategically aligned with business objectives.
