A growing part of the Bittensor community is framing the current pullback in $TAO as more than just another market dip. The discussion picked up after Andy, a Bittensor-focused commentator with over 10,000 followers on X, shared a thread arguing that $TAO trading below $300 reflects a disconnect between price and where decentralized AI adoption actually sits in its cycle.
The timing of that argument is important. $TAO’s price action has been weak for months. Since the halving, the chart has struggled to find footing. This week alone, the TAO price dropped another 20%, pushing price closer to the $200 level. Momentum remains clearly bearish, and there is no technical confirmation that a bottom is in place.
That context matters, because this conversation is not driven by charts or short-term setups. It is driven by how early the broader AI market still appears to be.
Andy’s core point focused on execution rather than narratives. He highlighted data from McKinsey showing that while a large majority of companies now claim to “use AI,” only a small fraction are seeing real economic impact. In his words, most firms are still “experimenting, not producing.” Less than one-third have moved beyond pilot phases, and only a single-digit percentage report meaningful EBIT contribution from AI initiatives.
This gap between perception and reality shapes the broader thesis. After years of hype and trillions spent on centralized AI infrastructure, production-level deployment remains limited. Most enterprises are still locked into a handful of centralized providers, relying on single-vendor stacks that prioritize convenience over competition.
McKinsey is showing us the biggest LIE in AI right now.$TAO under $300 isn’t a trade.
— Andy ττ (@bittingthembits) December 23, 2025
It's the opportunity of our lifetime.
Many think we are late.
We’re not. We’re unbelievably early.
After years of hype and TRILLIONS spent…94% still haven’t figured it out.
88% of… pic.twitter.com/Pm1J8eO4h7
From that angle, Andy argued that if the market is still early for centralized AI, it is even earlier for decentralized AI. Bittensor’s design, built around permissionless subnets that compete to deliver specific AI services, targets a later phase of adoption. That phase only begins once companies move past experimentation and start rethinking workflows at scale.
The distinction is important because it explains why price action and fundamentals currently feel disconnected. Infrastructure tends to be built before demand fully arrives. Historically, many foundational technologies looked unnecessary or overly complex until adoption caught up. The internet, cloud computing, and mobile platforms all followed that pattern.
At the same time, the market is clearly not pricing this as a certainty. TAO’s post-halving performance reflects skepticism. Liquidity has thinned. Volatility remains elevated. Price is well below prior highs, and buyers have shown little urgency so far.
That is why the “rare opportunity” framing remains a viewpoint, not a conclusion. It assumes that decentralized AI infrastructure eventually becomes relevant at scale and that Bittensor captures a meaningful share of that future demand. Neither outcome is guaranteed, and the market’s current pricing reflects those risks.
For now, $TAO under $300 means a debate more than a signal. On one side is weak price action and fading momentum. On the other is the argument that decentralized AI has not yet reached its adoption window. Which side proves right will depend less on sentiment and more on whether real usage, revenue, and on-chain demand begin to show up over time.
Until then, the divergence between price and narrative remains unresolved.
Read also: Bittensor (TAO) vs. Hedera (HBAR): Which Altcoin Could Perform Better in 2026?
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