From Copilots to Coworkers









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The shift from copilots to agents is the biggest change to technology work since the cloud. AI agents now write and test code, triage incidents, draft documentation, and run IT workflows end to end — which moves the bottleneck from producing software to specifying, reviewing, and governing it.
Alex Goryachev shows CTOs, CIOs, and engineering leaders what that means for team topology, platform strategy, and the operating model: smaller teams with agent leverage, new definitions of senior talent, and roadmaps measured in weeks instead of quarters.
Giving software the ability to act raises hard engineering questions: identity and least-privilege access for agents, observability and evaluation, cost control, and a security model where agentic AI is both your newest defense and your newest attack surface.
Alex's technology keynote turns those questions into an actionable architecture and governance agenda — what to build versus buy, how to take pilots to production responsibly, and how to set guardrails engineers will actually adopt. His perspective is informed by shaping ISO standards on innovation and working with the California State University system on AI and AI governance.
Alex is one of them. As Cisco's Managing Director of Innovation Strategy, he ran a $1.1B portfolio and built innovation centers across 14 countries — shipping technology transformation inside a global engineering organization, not theorizing about it. He has delivered keynotes for technology leaders at companies including Cisco, Dell, and IBM, is the WSJ-bestselling author of Fearless Innovation, a Forbes contributor, and a LinkedIn Top AI Voice, with 310+ keynotes and a 98% would-recommend rating.
Explore related keynote programs: Innovation & Entrepreneurship, Financial Services, HR & Talent
Ready to lead your engineering org into the agentic era? Work with Alex.
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According to a World Economic Forum report, 97 million new AI-related roles will emerge by 2025, while many current jobs will become obsolete without reskilling efforts.
Institutions must urgently invest in AI education to prepare both educators and students for this transformation. Without a skilled workforce, organizations risk falling behind in adopting AI technologies, limiting their ability to compete and innovate in a global market increasingly driven by AI advancements.
NSF is boosting AI research in academia with up to $500M in funding. Discover how this opportunity could shape the future of education and innovation.








Everybody knows we must embrace AI innovations, but how do we do this the right way? As AI tools rapidly transform education, addressing the challenges surrounding their use has become paramount.
Studies show that nearly 25% of students have turned to AI tools like ChatGPT for “academic assistance”, making plagiarism increasingly hard to detect, with detection tools often generating false positives. To navigate this new landscape, institutions must adapt to implement AI in a responsible way that helps meet academic goals. Addressing key issues is critical as AI reshapes the way we teach and learn.








Research shows that 70% of change initiatives fail due to employee resistance or lack of management support. In the context of education, AI is often met with skepticism, as faculty and staff worry about job displacement and the ethical implications of AI tools.
To overcome these barriers, it’s critical to build trust through transparency and clear communication. Institutions need to involve all stakeholders—educators, students, and administrators—early in the process, ensuring they understand that AI is here to enhance their work, not replace it, while strictly adhering to academic standards.








