Post: The rise of autonomous AI: How intelligent agents are redefining strategy, risk & compliance

Legacy methods started with the process and many AI controls today start with algorithms; but for agentic AI, proper oversight requires a phase shift that must start with the data

The rise of generative AI (GenAI) has been the momentum moving corporate and research expectations, investments, and innovation regardless of industry or discipline. However, in just two short years — and even without extensive scale and maturity of GenAI production systems — new variants and challenges are already alternating deployment designs and operating strategies.

In fact, 92% of companies say they will invest more in Gen AI over the next three years, yet only 1% state that their investments have reached maturity, according to a recent workplace report from McKinsey & Co.

For leaders currently struggling with the terminology and designs of GenAI — protocols, messaging, large and small language models, vector databases, algorithms, and more — a next generational shift is already underway. And it’s already building on top of early directions, while introducing a new set of requirements and governance demands. Will the AI momentum slow down? Will new AI innovations become mere extrapolations of early-stage data and intelligence advances? Or will something more profound happen?

Indeed, this pace of AI change is dwarfing anything previously experienced. However, what struck me is the question: How do you instill robust oversight for solutions which are temporal, self-learning, and adaptative based on the data they ingest? Everyone has their own understanding of what AI is from the daily blast of media articles, so baselining is necessary.

In 2023, the term pre-training took on new importance as ChatGPT permanently changed the discussion of systems and data — in addition to costs, cloud architectures, and skills needed. By mid-2024, enterprises were witnessing the rise of retrieval augmented generation (RAG) using external data to improve the accuracy of GenAI and their industry’s large language models. Now as 2025 emerges, corporate leaders are being blanketed with yet another evolution or iteration of GenAI — agentic AI . agentic AI To understand the progression of the question, What is AI? you need to compare the ideas of accountability and […]

The rise of autonomous AI: How intelligent agents are redefining strategy, risk & compliance