Where's the money đ° in Gen AI today? Just look at the top earners - 6 out of 10 are either hyperscalers or their partners, with Microsoft Azure ($3.9B ARR) and OpenAI ($3.4B) leading the pack.
đł But it's not just about revenue
Generative AI could be a game-changer for operational efficiency
In the recent earnings call, Microsoft claimed "hundreds of millions" in customer support savings,
while Amazon highlighted "$260 million and 4,500 developer years" saved in code migration.
As more companies lean into Gen AI, expect to see similar efficiency gains in the key areas where AI is already good enough.
đĄ What's the takeaway for the tech ecosystem?
Partnering with hyperscalers could be the key to hypergrowth.
Top clouds are fighting for dominance and becoming the de facto orchestrators of the AI ecosystem.
Despite market fluctuations, hyperscalers remain all-in on AI infrastructure.
Amazon's Andy Jassy put it bluntly: "while we're investing a significant amount in the AI space and infrastructure, we would like to have more capacity than we already have today."
Hyperscaler commitment to (over?) building will enhance access and reduce costs for everyone.
For partners, aligning with hyperscalers can unlock client access, resources, and growth opportunities.
Because of their central role, making it simple to buy, customer trust and (importantly) cloud commitments, customers will gravitate to them for deploying cutting-edge enterprise AI applications.
At the same time, hyperscalers are actively searching for new AI products to plug into their platforms to serve incredible customer demand in AI.
Thatâs why 47% of SaaS companies leverage cloud marketplaces.
đ Beyond hyperscalers
The AI ecosystem is diversifying. Sapphire Ventures recently stressed "a broadening of categories with GenAI products at $25M, $50M, and $100M+ scale."
From coding copilots to marketing copy generators, AI is quietly transforming industries.
But let's not get carried away by the hype
Today, inflated expectations are giving way to the realities of technology deployment timelines.
Shipping AI products is difficult regardless of the layer of the tech stack.
Patience is still required for the overall deployment of generative AI.
đ¤ Aligning with hyperscalers is a smart play in AI today, because this is where customers' hearts and wallets are.
Still, cloud marketplaces arenât the only path to win.
The question is, how will you position yourself to ride the Gen AI wave to follow the customer and without getting swept away by the hype?
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