Drowning in AI Tools? You're Not Alone

The enterprise AI space has a dirty little secret: everyone’s buying bots, and no one knows what the hell to do with them.

There are tens of thousands of new AI point solutions (agents, copilots, bots, widgets, and “magic” assistants) flooding the market every year. Some are incredible. Most are redundant. And nearly all of them are being adopted in isolation — leading to stack bloat, decision fatigue, and a tangled mess that IT teams lovingly refer to as "AI soup."

So, we did the research.

Here’s what you need to know if you're leading AI strategy in a mid to large enterprise — or trying to stop your company from becoming a cautionary tale on the next industry panel.

🧩 What’s Actually Happening Out There?

• 43,000+ AI startups launched in 2023 alone. That’s not a typo.
• Slack dropped 25+ GenAI apps in a single update.
• The average enterprise now runs 85+ SaaS apps — and AI tools are rapidly inflating that number.
• By 2028, AI agents will handle 68% of customer service interactions.
• $236 billion is the projected size of the AI agent market by 2034.

It’s a gold rush — and everyone’s got a shovel.

🧠 The Tool Problem Nobody Wants to Talk About

Let’s be brutally honest.

Enterprises are collecting AI tools like they’re Pokémon. Each department buys its own “must-have” agent or assistant. None of them talk to each other. And IT is stuck duct-taping them into legacy systems while execs wonder why their AI investments aren’t printing ROI.

Some common side effects:

• Tool overlap: Three different bots that all summarize emails.
• Shadow IT: Teams deploying tools outside governance frameworks.
• Integration hell: None of the tools play nice with core workflows.
• User fatigue: Employees stop using anything new.
• Security gaps: Random agents connecting to sensitive systems with zero oversight.

And let’s not forget the internal chaos: Marketing bought a copy bot, ops wants an AI analyst, finance is trialing an agent they found on LinkedIn, and Legal? They just want plausible deniability.

🤖 Specialization Isn’t Always Strategic

Some argue that more tools = more agility. Nice idea. Here’s the reality:

• Most AI tools are single-function and deeply siloed.
• 1 in 3 execs say their GenAI rollout has been a “massive disappointment.”
• Only 30% of enterprises are seeing meaningful ROI from these tools.
• The rest are wasting budget on bots that sit unused — or worse, generate chaos.

🔍 What Smart Companies Are Doing Instead

The ones getting it right? They’re not chasing every new shiny AI widget. They’re building frameworks for decision-making.

Here’s how they win:

1. Inventory everything: Know what’s running, what it does, and who owns it.
2. Rationalize the stack: Cut overlapping tools and consolidate where possible.
3. Favor platforms over point solutions: If your core software has AI baked in, use it.
4. Invest in integration: Half your ROI lives in how well these tools talk to each other.
5. Create internal AI champions: People who can vet, pilot, and roll out tools with purpose.
6. Measure everything: Track adoption, outcomes, and usage like your job depends on it (because it does).

💡 Likeable’s Take

At Likeable AI, we believe most companies don’t have a tech problem — they have a governance problem disguised as a tooling mess.

You don’t need 14 different copilots. You need one strategy, built on orchestration, traceability, and interoperability. That’s why we built our frameworks to work across the chaos — not add to it.

We help enterprise leaders:

• Score and prioritize tools based on impact.
• Build AI-ready architectures with open integration lanes.
• Create living dashboards to track actual business outcomes.
• Replace AI noise with AI discipline.

Tool sprawl isn’t a tech issue. It’s a leadership issue.

🧠 TL;DR (For the Scroll-Happy)

• The AI tool market is exploding — fast and messy.
• Most enterprises are overwhelmed and underperforming.
• Consolidation, governance, and integration are now competitive advantages.
• You don’t need more bots — you need better orchestration.

👀 Thinking about cleaning up your AI mess? Let’s talk before your next pilot turns into your next problem.

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