Adopting more intelligent machines is not the only aspect of the next stage of corporate AI. It’s about knowing what intelligence a firm should own and what it should rent, and whether its people and its organization can change as it does so.” Businesses are beginning to pose a different query: which aspects of our intelligence ought to be ours?
Artificial intelligence is moving from an emerging technology into a general-purpose capability embedded across business, government and society. As organisations increasingly use AI to make recommendations, generate content, analyse information, automate processes and take actions on behalf of people, governments are moving beyond voluntary discussions about AI ethics and beginning to establish formal systems of governance.
75 percent of industry respondents leveraging AI for tasks such as fraud detection and credit risk modeling. Yet, the rise of generative AI and agentic AI is what truly captures the imagination. Generative AI, despite only gaining traction since 2022, is now used by 71 percent of industry respondents, while agentic AI is already in active adoption among 52 percent. Fintechs, unburdened by legacy systems, lead the charge, with 57 percent adopting agentic AI compared to 45 percent of traditional financial institutions.
Generative AI has evolved well beyond a productivity tool; millions now use conversational AI for companionship, emotional support, coaching and, in some cases, long-term romantic relationships. What began as question-and-answer systems have become increasingly human in their language, personalities and ability to maintain context over extended conversations. i
Every generation has feared that the latest technology would spell the end of human memory. Socrates warned that the advent of writing would create intellectual laziness, a concern later directed at the printing press, newspapers, search engines and, most recently, artificial intelligence. While this anxiety is not entirely without foundation, the neuroscience of memory offers a more subtle perspective.
AI Agent Registry – a layer of customisable rules, sanctioned tools, and a registry to track ownership and activities of every AI agent deployed across the public service. Not a policy paper. Not a framework for consultation. Infrastructure. Who owns the agent? What systems can it access? What decisions is it authorised to make? And how can those actions be audited after the fact?
Human cognition is not a single linear capability that peaks and then deteriorates uniformly. Certain forms of rapid computational thinking do decline over time. But higher-order cognition often develops later because it depends upon accumulated abstraction layers built through experience, failure, pattern recognition, emotional calibration, and long-range consequence mapping
They’re B2B/prosumer tools targeting students, researchers, and academics: a smaller, quieter market compared to the consumer AI boom. They don’t have the marketing budgets or hype cycles of OpenAI/Google/Anthropic, and they rarely make splashy product launches.
“Workshop,” an open-source, MIT-licensed debugging and evaluation tool aimed squarely at the emerging era of agentic AI systems. The system functions as a local daemon and UI layer that captures full execution traces as they happen. Developers can replay an agent’s behavior, inspect failures, and pinpoint where reasoning or execution went off track.
