In this edition of Konversation, we look at the growing divide between enterprise AI licences and internally-built platforms, why physical AI ROI is now being audited rather than assumed, and the gap between what enterprises buy and what they actually use. Keep reading to know more.
Top 3 Market Insights:
- AI Knowledge Continuity Is Becoming a Buying Criteria: A concern we heard directly from a couple of CIOs is – what happens to AI knowledge when key IT people leave? With attrition high in AI and data teams, the question of who understands the system after a departure is now shaping vendor selection. This highlights the importance of mature IT processes and documentation-driven delivery. It’s a real differentiator now in many industries.
- Physical AI Meets the Bottom Line: For plant-level AI running for more than a year, leaders are still confused on ROI. For example, when asked about equipment effectiveness improving by 25%, leaders often can’t say how much AI contributed. Sensor rollouts, process changes, and AI may have all contributed. But at yearly renewal, how do you attribute AI value to your CEO/CFO? We’ve helped clients implement Physical AI and track 12 months of downtime data to clearly measure its impact. To know more, talk to our Delivery Head, Sajal.
- Most Enterprises Use a Fraction of AI They Bought: One thing that surfaced repeatedly from executive interactions is that in many enterprises, large AI and data platforms are running at a small share of their actual capability, sometimes as little as 5%. Meanwhile, the upstream/downstream problems businesses actually care about sit untouched. In healthcare, video information is often reduced to a small set of measurements rather than fully used for clinical decision-making (in which case AI spend can be cut significantly). An audit from a specialized AI firm is important to optimize AI capacity, usage, and costs.
Konverge.AI – Under the Hood
Our Work Highlights:
- We’re Now an OpenAI Select Partner: Konverge AI has joined the OpenAI Partner Network as a Select Partner. For our clients, this means frontier models applied to real workflows, agents that make it past the pilot stage, and enterprise guardrails built in from day one. The model was never the hard part, everything around it is. Reach out to discuss what this opens up for your AI roadmap.
- AI Leadership Xchange – Dallas Recap: Our Dallas roundtable was a huge success, in which CXOs and technology leaders got together on August 27 and there was a very interesting discussion on what could stop organizations from investing in AI over the next 3–5 years? Another most interesting thread was a panel discussion on ‘Funding the AI Agenda: AI Investment Priorities for 2027’. To know more, check the full event recording (to be out soon).
Want to build a token optimization strategy for your org? Reach out.
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