Artificial intelligence executives expect 2026 to mark a shift from today’s conversational and generative systems towards agentic AI that can act autonomously in cybersecurity operations and digital marketing.

Two founders working in cyber risk and local search forecasting say the coming phase of AI development will intensify competitive pressure on service providers and brands whose data is not ready for automated decision-making.

Agentic AI describes systems that can interpret information, decide on a course of action and execute tasks with limited human intervention. Industry leaders expect early deployments across cyber defence, managed security services and search-led customer acquisition.

The comments align with a broader industry move towards AI agents that sit on top of existing tools and datasets and that integrate into operational workflows in security operations centres, marketing platforms and customer service environments.

Venture funding has flowed into agentic AI infrastructure and orchestration over the past year. Large technology vendors have also begun to add agent-style automation features on top of their generative AI stacks.

Executives see this next phase as a structural change in how organisations handle risk and reach customers.

Cyber shift

David Primor, CEO and Co-Founder at Cynomi, expects agentic AI to reshape the daily work of cybersecurity teams and managed service providers.

He predicts a move away from tools that only generate content towards systems that can manage risk workflows end to end inside organisations of different sizes.

Primor draws a distinction between current generative models and the kind of agentic systems he believes will gain traction in 2026.

“We’re at a tipping point in a new AI era. In 2026, I believe we’ll move from generative AI – which creates text, code, or reports – to agentic AI, where systems act intelligently on data to assess, manage, and remediate cyber risks. Unlike traditional generative tools, agentic AI can interpret information, make decisions, and carry out tasks autonomously. In cybersecurity, this means AI will not just flag vulnerabilities or draft recommendations, but it will assess risks in real time, prioritize what matters most, and initiate remediation steps where appropriate. This evolution will fundamentally change the way cybersecurity operations work. Service providers who struggle with alert fatigue, talent shortages, and increasingly complex threat situations will get technology that acts as a true force multiplier. Agentic AI will allow teams to respond faster, scale their services without increasing headcount, and deliver more consistently strong outcomes for clients. It will also unlock a more proactive approach to cyber defense, shifting organizations away from reactive workflows to continuous, automated protection. In short, 2026 marks the start of the cybersecurity systems that do not just advise but act. Companies that adopt AI early will get an advantage in efficiency and client trust,” said David Primor, CEO & Co-Founder, Cynomi.

Security operations centres already face high alert volumes, a shortage of experienced analysts and a steady rise in the complexity of attacks. Vendors and service providers have begun to incorporate machine learning and automation into incident triage and response playbooks.

Agentic AI would extend these approaches. Systems could analyse asset inventories, vulnerability scan data and threat intelligence feeds, and then trigger predefined remediation workflows or ticketing processes without human initiation.

Managed security service providers could embed agents across client environments. These could carry out tasks such as configuration checks, patch orchestration and access reviews on a continuous basis.

Regulators in several markets have raised questions about the accountability and audit trails of automated decision-making in critical security functions. Organisations that deploy agentic AI will likely need detailed logging and human oversight structures around automated actions.

Search and brands

David Hunter, CEO at Local Falcon, expects similar agentic behaviour to transform how consumers and businesses search for information and discover local services.

Generative search interfaces have started to sit on top of traditional web indexes and local listings data. Users can ask natural language queries and receive summarised answers without clicking through multiple pages.

Hunter said this trend will intensify as assistants switch from returning answers to executing tasks for users.

“AI is rapidly shifting from just conversation to a fully agentic assistant that can take action on your behalf. When searching for something, most people no longer sort through endless tabs to find their answer. Instead, they ask AI for exactly what they are looking for and get exact, instant, tailored answers. As this trend continues to evolve, companies across all sectors will need to ensure their data is clean, consistent, and easily understood by AI models. Those that don’t will gradually disappear from the results AI presents. When agentic AI begins to make decisions for you and carry out tasks autonomously, real-time accuracy will be crucial. The brands that adapt and make themselves easily discoverable and scannable to AI systems will be the ones to lead in 2026,” said David Hunter, CEO, Local Falcon.

Local search and listing optimisation providers have already adjusted their tools for AI-driven discovery across search engines and mapping platforms. Agentic assistants could go further by booking appointments, placing orders or selecting service providers on a user’s behalf.

Brands risk losing visibility if their product and location data is inconsistent across sources. AI systems that assemble answers from multiple datasets may favour entities whose information is structured and machine-readable.

Digital marketing teams may need closer coordination with data engineering functions. They may also need new performance metrics focused on how often AI agents select or recommend their brand, rather than on traditional impressions and clicks.

Industry observers expect early adopters of agentic AI in cybersecurity and search-led marketing to influence standards for automation, explainability and data quality across other sectors.