Hello, dear readers!

This is our weekly brief on remarkable AI topics, so you can always stay in the loop.

Today’s focus — Accenture employees' careers are at stake because of AI, though not in the way you think. The consulting giant is reportedly tying leadership advancement to use of artificial intelligence. “Accent on the future” — and everything else can burn in the rear-view mirror.

Also in this week's edition:

AI or Goodbye

According to reporting by The Guardian, Accenture is now linking senior promotions to regular use of its internal AI tools. Not just “familiarity.” Not just “awareness.” Actual, trackable usage — weekly log-ins included. The message is subtle like a sledgehammer: if you want to lead, you’d better be prompting.

The consultancy has pledged to train 550,000 employees and is investing roughly $1 billion a year in learning initiatives. CEO Julie Sweet has made it clear that AI capability is becoming central to performance expectations. Those who don’t adapt may find themselves… adapting elsewhere.

Accenture began positioning itself as a global AI frontrunner last year — going so far as to rebrand its workforce as “reinventors.” In September, Sweet signalled that employees failing to embrace AI tools could be “exited.” The phrasing raised eyebrows: part tough-love transformation memo, part cringe dystopian HR-speak.

Whether this hard pivot cements Accenture’s leadership in enterprise AI — or earns it a spot in the cautionary-tales folder — remains to be seen. A report published last year by Orgvue suggests many executives are already nursing second thoughts. While 39% of companies said they cut staff due to automation, 55% of those now admit they moved too quickly. Confidence in AI-driven job displacement is also softening: only 48% of leaders expect significant redundancies, down from 54% the year before.

In other words: even as companies push AI deeper into performance metrics and promotion criteria, the broader corporate mood is less triumphalist than it was 12 months ago. Accenture’s gamble is clear — make AI fluency non-negotiable. The question is whether this produces a generation of genuinely AI-native leaders — or simply a workforce that logs in because HR is watching.

India Writes a Very Large Cheque

At the India AI Impact Summit, ambition was not in short supply.

Domestic conglomerates Reliance Industries and Adani Group reportedly outlined a combined ~$210 billion in AI data centre and infrastructure investments. Meanwhile, global players including Microsoft, OpenAI, Nvidia, AMD, and Blackstone signalled capital expenditure that could reach eye-watering levels this year.

Backed by chip incentives and closer cooperation with Washington, New Delhi is clearly aiming for superpower status in AI. The strategy is infrastructure-first: build the compute, attract the capital, then scale the ecosystem.

But the story isn’t only about hyperscale data centres and geopolitics. It’s also hyperlocal. At the summit, Sarvam AI unveiled Indus — a would-be competitor to OpenAI’s ChatGPT — with one notable edge: support for 22 Indian languages.

Rather than chasing generic global benchmarks, Indus is built specifically for India’s linguistic and cultural complexity, with regional knowledge baked in. In other words: not just bigger models, but models that actually speak the country’s many tongues — fluently, and on their own terms.

When the Shopper Is an Agent

A new Harvard Business Review piece explores a scenario that feels less speculative by the week: consumers delegating product search — and increasingly, the purchase itself — to AI agents. The human scrolls less. The machine decides more.

For brands, this changes the game. You’re no longer persuading a distracted person with vibes, visuals, and impulse triggers. You’re feeding a parsing engine trained to rank, filter, and compare at scale.

The prescription? Build a “trust layer” for agentic commerce. That means structuring product data so machines can actually interpret it — call it AIEO, AI Engine Optimization — setting explicit consent and usage boundaries, monitoring how your brand is represented across AI platforms, and having a rapid-response plan for when automation inevitably goes sideways.

The takeaway is less sci-fi than operational. If AI-driven shopping scales — and signs suggest it will — trust becomes strategy. Your next customer might not have emotions. But it will have a ranking algorithm.

Thanks for reading AIport. Until next Monday — by then, AI will definitely do something we can't possibly expect.