Conviction at CES 2026: 'AI will surpass past technological revolutions'—CFO vs. CIO, job polarization, and the reason 'VCs are buying hospitals'

What was discussed at the CES 2026 venue was not just the 'next trend in generative AI.' In a public discussion on the All-In Podcast, host Jason Calacanis provocatively declared that the impact of the PC, internet, mobile, and cloud over the past 30 years 'looks small (dwarfed)' compared to AI. Joining the discussion were Bob Sternfels, Global Managing Partner at McKinsey, and Hemant Taneja, CEO of General Catalyst. On Apple Podcasts, this episode is also organized under the theme: 'Why AI will surpass past technological revolutions: Robots, manufacturing, and AR glasses.'

The following is a breakdown of the key points of this long-form talk from an 'investor and business perspective.'

1. 'AI is the greatest social transformation'—'Speed' rewrites everything

The keyword they repeated was the speed of change (organizational speed / warp speed).Taneja calls the last few years 'peak ambiguity,' explaining that not only technology but also geopolitics, industrial policy, and alliances are being shaken simultaneously. The important thing is that 'what can be built' is being updated not in terms of years, but in terms of weeks to months.

In the world of investment, this becomes 'compression of value creation.' In the past, the metric was 'how many years until $100 million in revenue?', but now, 'the arrival is so fast that the comparison axis itself collapses.' This feeling is directly linked to the next topic (valuation and industrial restructuring).

2. 10x growth and the 'not a bubble' argument—Corporate adoption is the fuel

Taneja spoke of the rapid growth of AI companies not as mere expectations, but as the 'rise of real demand.' In fact, there is a trend where prominent VCs argue that 'AI is a fundamental change on a level equal to or greater than the internet, and looking at it only as a bubble misses the essence.'

On the other hand, Sternfels presents a more 'field-oriented' view. Large companies have started using AI, but it is more difficult than imagined to 'scale value' in non-tech companies. In other words,

• Adoption is fast (PoCs are proliferating)

• However, it is difficult to establish (ROI is not achieved, the organization does not change)
  —this 'implementation gap' will be the biggest bottleneck.

3. CFO vs. CIO—'Financial caution' and 'Technical urgency' collide

Sternfels pointed out the 'division' occurring in modern board meetings.

• CFO: 'We invested, but I don't see the ROI. Let's stop for now.'

• CIO: 'If we don't do it now, we will be disrupted. If we stop, it's over.'

The solution discussed for this conflict was to treat AI not as 'tool introduction,' but as a redo of business design and organizational design (reorg / change management). In other words, AI investment is becoming a budget for 'business model renewal' rather than an IT budget.

4. 'VCs buying hospitals'—The strategy of buying the castle and lowering the drawbridge

This was the most provocative point. Taneja explains the reason General Catalyst acquired an Ohio-based healthcare system (Summa Health) as 'securing market access (adoption sites) for startups ourselves.' This is not 'PE-ization,' but the idea of buying the actual site of implementation to change industries that are difficult to transform with AI (such as healthcare).

This Summa Health acquisition has been tracked by multiple media outlets and was reported to have closed in October 2025. (The structure of VCs buying hospitals itself also became a major point of discussion.)

What is important from an investor's perspective is that the change happening here is not a 'SaaS sales competition,' but a rewriting of the industrial structure itself. AI cannot be won with just a 'good product'; those who control adoption, regulation, and on-site operations are the ones who are strong. Healthcare is a symbol of this.

5. Jobs will 'split' rather than 'decrease'—The polarization shown by the McKinsey example

The conversation about employment can turn either pessimistic or optimistic. However, what makes this discussion interesting is that it is not about 'simple layoffs,' but rather that 'growing departments' and 'shrinking departments' are occurring simultaneously within the same company. Sternfels mentioned that even within McKinsey, tasks are being redistributed due to AI utilization, and external reports have highlighted the reality where 'personnel (humans) and AI agents coexist.'

The practical implications that can be derived from this are clear.

• Entry-level tasks (searching, summarizing, document creation) will become increasingly automated

• On the other hand, upstream tasks (designing questions, decision-making, creativity, co-creation with customers) will become even more important

In other words, rather than jobs 'disappearing,' the 'bottom rungs of the ladder' are thinning out, while the value of the upper rungs is increasing.

6. The next main battlefield is 'Physical AI'—autonomous driving, manufacturing, robotics, and AR

The latter half of the discussion moves from software to the real world. While autonomous driving will see 'experience spread first,' the view was expressed that robots (especially humanoids) might see slower adoption than imagined, as hardware supply and manufacturing capacity become bottlenecks. What is essential here is that the AI race will be a battle not just of 'model performance,' but of manufacturing, supply chains, and cost curves.

Furthermore, AR glasses were discussed, citing Google Glass as a 'future that arrived too early,' as a lesson that 'even if the form factor improves, they will not be adopted if the utility (essential use case) is immature.'

7. Summary—3 points that investors and business professionals should watch now

1. AI adoption is 'organizational transformation,' not an 'IT initiative': The conflict between CFO and CIO can only be resolved by revamping the management model.

2. The winning strategy is shifting from product to 'adoption path': Like buying hospitals, moves to secure the front lines, regulated industries, and distribution channels will increase.

3. Employment will polarize, and skills will shift toward 'questioning, judgment, and co-creation': In the AI era, the difference will be made by 'whether you can create good questions' rather than the amount of knowledge.

The message this session drove home is simple. AI is not a 'new feature,' but a platform that rewrites the blueprints of industry. That is precisely why they argued it appears larger than past technological revolutions.

Recommended Articles

Next Big Wave (Growth Stocks, Seeds of Ideas, Deep Dives into Trends)