Understanding Investment, Value And Business Impact

by Linda

Salim Gheewalla, Founder & CEO, utilITise self-healing IT.

Artificial intelligence is no longer a buzzword—it’s a battleground. AI is embedded in everything from code to conversations, and while media headlines race to cover the next breakthrough, most executives are still trying to make sense of what AI actually means for their business.

Here’s my take, broken down across five strategic vectors that define AI’s real-world business impact.

1. AI Brains: Foundation Models Become The Platform

The emergence of foundation models like GPT-4, Claude and Grok democratized AI intelligence. But in 2025, these models have shifted from novelty to necessity. Anthropic, for example, closed a $13 billion round and hit a $183 billion valuation. GPT-4 isn’t just writing blogs; it’s embedded in sales tools, security workflows and enterprise-grade copilots.

APIs make it possible to plug into intelligence on demand. In a sense, it’s like having a cognitive contractor that doesn’t sleep. Businesses that used to ask “Should we build our own model?” are now asking “Which one can we fine-tune to drive revenue or reduce cost?”

2. Hyperscalers: Infrastructure As A Board-Level Strategy

The capital arms race is staggering. Microsoft, Google, Amazon and Meta, together, have spent over $155 billion on AI-related infrastructure this year alone. McKinsey projects global AI-related data center spend to hit $5.2 trillion by 2030.

This isn’t just about compute. Hyperscaler investment is lowering the barrier for enterprises to deploy AI at scale. You don’t need your own GPU cluster; you need the right hyperscaler partner with the right service level agreements (SLAs) to bring AI-powered agility to your business.

3. Enterprise LLMs: Owning Intelligence Where It Matters

For companies with proprietary data and sufficient complexity, building or fine-tuning large language models (LLMs) in-house is increasingly proving its value. What once started as experimental pilots are now becoming integral platforms that drive core operations.

At the same time, new players are reshaping the landscape. CoreWeave locked in a $12 billion, five-year AI infrastructure deal with OpenAI. It’s not just the Googles of the world that are building. Enterprises that understand their domain deeply are developing models that reflect their competitive edge.

4. AI Wrappers: The Copilot Era Has Arrived

AI wrapper tools that make AI accessible to non-technical users are now front and center. Microsoft Copilot, Salesforce’s Einstein GPT (now Agentforce) and tools like Seamless.AI are boosting productivity across industries.

Salesforce alone reports that over 60% of users now interact with AI features. These aren’t just assistants. They’re becoming operational teammates. If AI brains are the engine, wrappers are the steering wheel. They bridge technical depth with practical use, giving business units the confidence to act on insights—not just stare at dashboards.

5. IT Infrastructure Integration: The Real AI Use Case

AI in IT isn’t flashy, but it’s deeply valuable. Predictive network analytics, AI-based threat detection, automated patching—these are the unsung heroes driving uptime and security.

IBM reports that AI-driven cybersecurity reduced breach response time by 108 days and saved companies over $1.7 million per incident. This is where AI quietly pays dividends.

Self-healing systems are now real. And as someone building a platform in this space, I can tell you this isn’t theory. This is day-to-day operations.

Where Business Leaders Should Focus

You don’t need a 40-person ML team to benefit from AI. Start where there’s friction—think revenue leakage, repetitive support tickets or overloaded analysts.

Most businesses will extract AI value in this order:

1. AI wrappers for instant productivity

2. AI infrastructure integration for resiliency

3. Hyperscalers for scale

4. LLM fine-tuning for IP leverage

5. Foundation model alignment for the long term

Simply put, AI is likely to become part of your business operations whether you like it or not. Just like those who resisted cloud adoption, the holdouts will eventually follow.

My advice? Take a step back. Look beyond ChatGPT prompts and gimmicks. Understand what AI can truly do across systems, workflows and outcomes. Once you grasp that, you won’t just use AI. You’ll realize how much it can elevate your entire business.

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