Immuta's CEO makes a compelling case that data security alone won't deliver AI ROI—governance must evolve to enable safe, scalable access. Practical shift or just buzz? How's your data strategy adapting?

IBM Tech analyzes Reddit's push against AI slop, stressing practical compute ROI as platforms favor quality over volume. Smart filtering could reshape AI investments. How are you optimizing your AI output strategy?

An AnswerRocket analyst just released the most honest breakdown of enterprise AI economics I have seen all year. The title says it all: AI intelligence is not free.

The video walks through the real total cost of ownership for enterprise AI deployments. Token costs, infrastructure, integration, change management. The math that vendors do not put in their pitch decks.

One number stood out: most enterprises underestimate their Year 1 AI costs by roughly 60 percent. Not because the technology is overpriced. Because they forget to account for the engineering time, the data cleanup, and the organisational friction required to make any AI tool actually deliver.

The thesis is uncomfortable but unavoidable. If you cannot model your full TCO and attach a specific metric to the output, you do not have an AI strategy. You have an expense.

Full video walkthrough below. Worth every minute of your time.

Are you tracking your real cost per token? Or are you still treating AI spend as a magic line item you cannot audit?

— Priya Sharma

An Oracle executive walked onto a stage in Sofia today and told a room full of executives something most AI vendors will not say aloud: ROI does not come from buying more tools.

Peter Baltadjiev, Executive and CS Board Chair at Oracle, joined Marina Tsekova on the Webit 2026 stage for a 17-minute reality check on enterprise AI — and it is exactly the kind of analysis every business leader needs right now.

The thesis is brutally simple. Most enterprises are still deploying AI as a technology purchase rather than an operating model transformation. That distinction — not the choice of model or cloud provider — is what separates the 5% that see real returns from the 95% stuck in the pilot graveyard.

The video covers the structural shift from hype to measurable impact: how to build a strategy that moves past proof-of-concept paralysis, what meaningful ROI metrics actually look like, and why the gap between "AI assists my team" and "AI runs the workflow" is the single biggest strategic differentiator this year.

Here is what I keep coming back to after watching this. When an Oracle board chair says the average enterprise is still in Year 1 of what McKinsey calls a multi-year compounding curve, it is worth asking yourself honestly: are you building genuine capability, or just adding to your SaaS stack?

Watch the full session from Webit 2026 and ask yourself the hard questions about your own AI strategy. The market will sort the real from the hype faster than you think.

— Priya Sharma

Every week, I get asked the same question by business owners: where do I even start with AI?

Alex Hormozi lays it out simply in this video — and that simplicity is exactly why most people miss it. His core message: stop using AI to do dumb things faster. Strategy first, tools second.

The most practical takeaway for any business leader? Walk into a traditional business, observe for free, and come back with an AI plan that saves them at least $100,000. Performance-based, zero risk for the client, and in 2026 this approach works because most businesses still do not know what to do with AI.

Here is what I want you to take from this video:
1. Start with the problem, not the tool. Identify your biggest cost centres — support, data entry, content production.
2. Measure before you automate. If you cannot quantify the baseline, you cannot prove the ROI.
3. Use AI to multiply output, not just reduce cost. Drafting, personalisation, and automation compound over time.

Hormozi says AI will never be worse than it is right now. The improvement curve is that steep. The businesses that win in 2026 are the ones building their AI muscle today, even imperfectly.

Watch the full breakdown and ask yourself: what is one process in my business that AI could handle better than a human?

-- Priya Sharma