As the AI race heats up, so does the battle for eyeballs

Cohere renamed Ottawa's EY Centre to the Cohere Centre after buying the naming rights, as part of a broader AI industry push to raise brand awareness and win customers. The company also expanded marketing through Magnus Carlsen ambassadorship and an Aston Martin Aramco F1 partnership, while peers like Anthropic, OpenAI and Google are using Super Bowl ads and sports sponsorships. The article is largely a strategic commentary on AI marketing spending rather than a direct financial or operational update.

Analysis

This reads as an early-stage land grab for mindshare, not near-term revenue, and that matters for positioning. The first-order winner is not the companies buying ads, but the ecosystem around enterprise AI adoption: firms with the deepest distribution, strongest trust signals, and cheapest customer acquisition will eventually convert brand spend into lower sales-cycle friction. That creates an indirect advantage for incumbents with already broad enterprise footprints, while smaller model vendors are forced to spend more just to stay visible.

The second-order risk is that this marketing race exposes who is running out of differentiation. When product quality is hard to discern and switching costs are low, companies substitute branding for proof of ROI; that tends to compress eventual margins because CAC rises faster than retention. The AI spend cycle can therefore look healthy for 6-12 months while simultaneously sowing the seeds of a more brutal consolidation phase over 12-24 months.

For GOOGL, the signal is mixed: AI marketing helps normalize AI as a consumer and enterprise utility, but it also intensifies the contest for default search and workflow surfaces. Google is unusually well placed if AI awareness expands overall, because it monetizes both attention and infrastructure, but the net effect depends on whether AI usage increases query volume enough to offset margin dilution in search. IBM is a cleaner beneficiary on the enterprise side if buyers become more skeptical of hype and prioritize governance, integration, and procurement-friendly vendors over pure-play narrative companies.

The contrarian read is that these sponsorships are less about confidence than about defensiveness. The companies with the weakest consumer pull need louder branding to avoid being commoditized, and the market may be overestimating how durable logo-driven differentiation is in enterprise software. If AI budgets tighten, marketing is one of the first line items to get cut, so these deals are more vulnerable than data-center capex to a slowdown in bookings or a rise in customer skepticism.

Key Decisions for Investors

• Long IBM / short a basket of high-spend AI pure plays over 3-6 months: IBM has lower need for brand theater and should benefit if buyers shift toward procurement-safe enterprise AI; risk/reward is attractive if the market starts rewarding durable revenue over awareness.
• Buy GOOGL on 3-12 month dips rather than chasing strength: the stock benefits from broader AI adoption and attention monetization, but position size should reflect margin pressure risk if AI features accelerate search cannibalization.
• Sell calls against existing long positions in richly valued AI branding-heavy names for the next 1-2 quarters: the market is likely to reward hype near term, but upside may be capped if sponsorship spend fails to translate into measurable pipeline.
• Pair trade: long enterprise software with governance/compliance exposure, short AI-first names reliant on paid mindshare, 6-12 months: the market may rotate toward vendors with clearer ROI proof as the marketing arms race matures.
• Set a catalyst watch on quarterly sales efficiency metrics across AI vendors over the next 1-2 earnings cycles; if CAC rises faster than net retention, fade the branding winners and extend shorts into the weakest balance sheets.