By Ambika Sharma
Many brands claim to be “using AI.” Few, however, have made the strategic leap that counts, treating AI not as a tool, but as a performance asset. The real shift isn’t just adoption, it’s accountability. Until AI is tracked like a revenue driver, it’s unlikely to behave like one.
We’ve moved past the era of sandbox experiments. AI today isn’t just automating tasks, it’s replacing inefficiencies, reducing waste, and delivering measurable growth. In high-performance organisations, AI is budgeted with the same scrutiny as media spends or product development: as an investment tied to outcomes.
Trained AI agents
Trained AI agents are leading this transformation. Intelligent systems, like Yukti, built for high-consideration product demos, are solving one of the most expensive gaps in enterprise and SaaS sales: ineffective pitching. Yukti delivers consistent, contextual demos at scale, 24/7, without fatigue or deviation. Beyond saving lakhs in direct costs, agents like Yukti rescue lost opportunity by closing gaps in sales readiness, multilingual delivery, and real-time response.
Then there’s the matter of brand visibility inside generative AI ecosystems. As large language models become the first point of discovery, traditional SEO falls short. NeuroRank steps in here, optimizing brand narratives within LLMs, not just on the open web. By ensuring accurate, persuasive, and discoverable responses in AI-generated content, NeuroRank not only protects reputation but also improves MQL quality, increases buyer confidence, and lowers acquisition cost.
Trained systems
This is what outcome-aligned AI looks like. Not chatbots for show. Not dashboard tools with vague metrics. These are intelligent, trained systems architected to impact the P&L.
And timing matters. The cost of AI inertia is already visible in the global market. NVIDIA surged while Intel hesitated. Meta realigned faster than Google. Apple redefined its category through on-device AI, while Samsung trailed. These weren’t just product plays, they were vision gaps. In each case, a delay of a few quarters translated into lost valuation, lost audience, and lost influence.
The same urgency applies now across mid-market and enterprise brands. Waiting another year to structure AI is not a neutral decision, it’s an active risk. AI ecosystems move faster than any platform shift before them.
The shift needed now is strategic clarity. AI is no longer a backend feature. If it drives conversion, improves demo effectiveness, safeguards brand identity, or reduces CAC, it must be managed like a performance asset.
Because here’s the reality: If your AI doesn’t move the business, it’s not strategic.
But if it does, then it’s no longer a tool.
It’s your next P&L line.
The author is founder and chief strategist, Pulp Strategy