Technology Trends & Roadmaps

Where the technology is heading, and what to do about it

The strategic view: which technology shifts are real, which are marketing, and how to turn that into a funded plan.

• The AI capability and cost curve - Why capabilities that were research projects two years ago are now commodity, and what that makes economically viable for attackers and defenders alike.
• Open-weight models vs. frontier labs, and the geopolitics — Open models now rival the leading Western systems at a fraction of the cost. What this means for sovereignty, data residency and vendor concentration - and why safety controls that exist at a provider disappear the moment a model runs on someone else's hardware.
• Agentic AI: software that acts, not just answers - Where autonomous systems are genuinely arriving, and the accountability, identity and liability questions that follow them into the enterprise.
• Quantum computing and the cryptographic clock - Why encrypted data stolen today becomes a liability long before quantum computers mature, which of your data has a long enough shelf life to matter, and what this means for budgets already committed to AI.
• Emerging research, technologies and use cases - What is moving from the research frontier into practical use across industries, and how to tell what is ready to fund from what is still a demonstration.

You will leave with a structured roadmap template and a clear view of where to spend and where to wait.

The New Offensive Landscape

How AI changed the economics of attack

Attackers did not get smarter. They got cheaper, faster and more numerous — and the AI tools your organization already deployed have themselves become targets.

• The economics of attack - How cost, speed and scale have shifted, and why attacks once reserved for high-value targets are now viable against everyone.
• AI-assisted and autonomous offensive operations - What automation has genuinely changed in real campaigns, and what it has not. Practical implications for your defensive timelines.
• Synthetic identity, and the end of language as a defensive signal — Voice and video impersonation in fraud and social engineering, and why the local-language cues your staff were trained on no longer work.
• Your AI systems as an attack surface - How AI assistants and agents can be turned against the organizations running them, and why this is not primarily a question of employee misuse.
• New dependencies and machine identities - The AI supply chain, and the rapid growth of non-human identities that hold real access and sit outside most identity programs.

You will leave with a clear picture of which threats have genuinely changed and which have not, and a set of questions to put to your own team.

Defense, Governance & Resilience

Controls, response and regulation when both sides are automated

Defenders cannot respond at human speed alone - but "add AI to the security team" is a slogan, not a strategy.

• Where AI genuinely strengthens defense, and where it fails - Realistic capabilities, honest failure modes, and where to place human judgment.
• Controls for AI you buy, AI you build, and unapproved AI that arrives unapproved - Practical measures built on your existing controls, not a parallel security program.
• Regulation: local obligations and export-driven requirements - What actually creates obligation for your organization, what your customers will demand regardless of regulators, and which certification paths are worth the investment.
• Incident response and forensics in AI environments - What evidence exists, what most organizations fail to retain, and how response changes when the adversary moves faster than your approval chain.
• Governance and risk in practice - Assessing AI risk inside your existing framework, and the minimum governance that actually ships.

You will leave with a practical control checklist and a view of which obligations apply to you.