Cathy Mauzaize, president of EMEA at ServiceNow, argues that organizations need agile leadership to get the most out of AI.
If the past few years were about understanding what AI can do, 2026 is about what will happen when AI becomes an integral part of the way we live and work.
The coming months will focus on embedding AI into the fabric of business operations, reshaping industries, rethinking customer experiences, and redefining the way people work.
Here are the four trends I think will define 2026.
Multimodal becomes the new norm
We have entered a new era of boundaryless work, where tools adapt to the way people think, speak, and create.
Modern enterprise UIs are multimodal by design. IDC predicts By 2028, 80% of enterprise AI systems are expected to be able to handle multiple types of input. Meanwhile, the London School of Economics recently predicted that Gen Alphas will no longer communicate with their bosses by email by the time they enter the workforce.
We don’t know if email will become obsolete anytime soon, but communication between emails and with AI won’t be limited to text. Voice, images, clicks, text, and video can coexist in one intelligent workspace, making every interaction feel natural, fluid, and intuitive. Instead of switching between disconnected apps, employees engage through one unified experience that understands context and intent.
This is already changing the way we work. AI takes notes, updates documents, and builds visuals in real-time, while your team can conversationally outline the project. Service agents move seamlessly between chat and voice, and AI predicts next steps and captures data instantly. Analysts can ask questions aloud and visually explore insights, all in the same place.
Governance and speed define leadership
As AI becomes central to how organizations operate, leaders will face an increasing challenge: how to maintain trust without slowing innovation. Across EMEA, the balance between governance and speed is becoming more important. AI Maturity Definition Measures.
of EU AI law This is a turning point that moves regulation from theory to practice. But rules alone cannot produce responsible AI. The real test is how organizations incorporate compliance into their daily operations and embed accountability and transparency into their workflows, data, and decision-making.
of oxford university AI Governance Annual Report 2025 We’ve found that leading organizations are building governance directly into their workflows, rather than treating it as a compliance exercise. In doing so, we maintain the speed of innovation while mitigating AI-related risks.
Successful leaders treat governance not as a brake but as a driver of trust and resilience. They build a culture where transparency, explainability, and ethical use are built-in rather than an afterthought. They use clarity to move faster, not slower. Achieving this requires a single, central platform lens of large-scale language models (LLMs), AI agents, and workflows.
This new era requires both discipline and agility. AI must be fast enough to drive innovation, yet tightly controlled enough to earn trust. Leaders who get this balance right will define the next stage of growth and prove that responsible AI and rapid progress can coexist.
CIO leads agent AI
As AI becomes more embedded, by 2026 we will see the rise of agent platforms, networks of intelligence that blend human and machine work to drive speed, accuracy, and innovation. These agents will increasingly manage workflows, simplify complexity, and work alongside humans to augment rather than replace human judgment.
But as this new layer of work evolves, so too will a new layer of risk. The challenge is over shadow ITbut Shadow AI – Models and agents developed outside the governance framework. This creates compliance, privacy, and security vulnerabilities. Regulations are evolving across the region, but innovation is already outpacing policy. CIOs and boards need to anticipate rather than react and stay one step ahead of regulatory changes to avoid future disruption. Agility is the differentiator.
Successful leaders succeed by adopting flexible, adaptable platform architectures that connect data, governance, and decision logic by design.
Work AI will be blended rather than siled within apps
By 2026, AI will no longer sit on the sidelines of work, but will flow through it. What started as an additional layer of efficiency has evolved into operational intelligence, helping organizations move faster, make better decisions, and focus on what matters most.
This evolution is not a transition from ChatGPT on mobile phones to enterprise desktops. It’s about learning how to work in a mixed environment where AI is seamlessly integrated into daily work. This relies on identifying appropriate AI practices for each specific use case. It then coordinates agents for each task to work together toward real business outcomes, supported by personalized industry, context, and business knowledge.
For individuals, this change is very personal. The most effective employees are those who can work fluently with AI, manage their own agents, prompt effectively, and know when to trust, question, or redirect automated output. Many organizations are already recognizing this by making AI proficiency part of their performance and evaluation metrics.
This is nothing new for a new generation entering the workforce. It will feel natural. They will expect to work with intelligent systems as part of how they get their jobs done.
Success for organizations will depend on how seamlessly this human-AI partnership can be realized, not just as a tool to deploy, but as an environment to learn.
by Kathy Mouseys
Cathy Mauzaize is President of Europe, Middle East and Africa (EMEA) region. ServiceNowresponsible for driving growth strategies. She previously held senior management positions at companies including Microsoft, SAP, Dell, PwC, and Hewlett Packard.
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