The Most Underrated Ways Businesses Are Actually Using AI Right Now

TL;DR

A Reddit thread asking about underrated AI use cases for real business tasks sparked 86 comments and genuine community discussion about how companies are quietly leveraging AI in ways that don’t make the headlines. The conversation reveals that the most impactful AI applications aren’t always the flashiest ones — they’re the boring, repetitive, behind-the-scenes workflows that suddenly become frictionless. From automating data updates via Telegram bots to generating presentations in seconds, the real ROI often hides in the mundane. If you’re still thinking AI is just for writing blog posts, you’re missing the bigger picture.

What the Sources Say

There’s a fascinating Reddit thread over in r/artificial that’s worth digging into. The post — “What’s the most underrated way you’ve seen AI used for actual business tasks?” — accumulated 86 comments and a score of 29, which tells you this isn’t just theory. Real people are sharing real workflows.

The community consensus that emerges from discussions like this one is consistent: AI’s biggest wins in business aren’t in the glamorous, customer-facing applications. They’re in the operational layer — the stuff that happens before a customer ever sees anything.

Here’s what the broader ecosystem of tools mentioned in this space tells us about where AI is actually being deployed:

The Unglamorous Winners

Workflow automation with a brain. Tools like Make and n8n have existed for years as no-code automation platforms — but pairing them with AI turns “if this, then that” into something far more powerful. Instead of rigid rule-based automation, businesses are building workflows that can interpret, classify, and route information intelligently.

Bots as internal interfaces. Telegram, typically thought of as a consumer messenger app, is being used by businesses as a lightweight interface for bot-driven data updates. This is genuinely clever: instead of building an internal dashboard or admin panel, you ping a bot, it queries your system, and you get structured data back — all from your phone. The infrastructure cost is near zero.

AI for research and document interrogation. NotebookLM from Google is getting serious attention for letting teams talk to their own documents. Legal teams reviewing contracts, analysts synthesizing market reports, HR teams parsing policy documents — this is practical, high-leverage work that doesn’t require any coding skills.

Presentation generation from a single prompt. Gamma represents an entire category of tools that compress a multi-hour workflow (research → outline → design → slide content) into minutes. For anyone who’s ever spent a Sunday afternoon building a pitch deck, this is not a small deal.

Tracking AI visibility. This one’s genuinely new territory. Tools like LimyAI focus on understanding which AI search engines and LLMs are actually surfacing your web content — and what prompts are driving those visits. As AI-powered search becomes the default for more users, knowing whether you’re visible inside an LLM’s response is becoming as important as traditional SEO rankings.

Where Things Get Interesting (and Slightly Contradictory)

The interesting tension in these discussions is always between build vs. buy. On one side, you’ve got polished SaaS tools (ChatGPT, Gemini) that are immediately usable but come with subscription costs that stack up. On the other, you’ve got open-source options like n8n (self-hosted) and PostHog that require more setup but give you full control and near-zero marginal cost.

For small businesses and solo operators, the stacking of multiple $10-$20/month AI tools can quietly eat into margins. For larger organizations, the calculus flips — the productivity gains dwarf the subscription costs.

There’s also an emerging awareness around AI search optimization that’s separate from traditional SEO. Tools like LimyAI signal that we’re entering a period where businesses need to think about their “LLM footprint” — whether they’re being cited, referenced, or surfaced in AI-generated answers — not just their Google ranking.

Pricing & Alternatives

Here’s a breakdown of the tools that came up in this discussion, with pricing as reported:

The value sweet spot for most small-to-medium businesses seems to be in the combination of a capable AI assistant (ChatGPT or Gemini at ~$20/month) paired with a workflow automation layer (Make at $9/month or n8n self-hosted for free). That’s a potentially transformative stack for under $30/month.

For teams that want to avoid vendor lock-in entirely, the n8n + PostHog + Telegram bot combination offers a genuinely powerful open-source alternative — though it does require someone comfortable with self-hosting.

The Bottom Line: Who Should Care?

Small business owners and solopreneurs should pay close attention to the automation angle. If you’re still manually moving data between apps, generating reports by hand, or spending hours on presentations, there’s a legitimate productivity leap available to you for a very modest monthly spend.

Marketers and content teams need to start thinking beyond Google SEO. The LimyAI category — tracking your visibility inside AI-generated responses — is early but important. If your customers are increasingly getting answers from AI assistants rather than search results, knowing whether you appear in those answers matters.

Operations and IT teams at growing companies will find the n8n and Make ecosystem genuinely useful. The ability to build AI-augmented workflows without engineering resources is a real capability shift. Pair that with Tailscale for secure internal networking and you’ve got a lean but powerful internal toolchain.

Executives and decision-makers should resist the temptation to only think about AI in terms of headline use cases (chatbots, copilots, content generation). The community conversation makes it clear: the underrated applications are operational, internal, and deeply unglamorous — and that’s precisely why they deliver outsized ROI. Nobody writes press releases about “we automated our internal reporting via a Telegram bot,” but someone absolutely should.

The pattern is consistent: the businesses getting the most out of AI right now aren’t necessarily using the most sophisticated tools. They’re identifying the highest-friction, most repetitive parts of their operations and systematically eliminating them. That’s not a technology story. That’s just good business sense — with a very capable new tool in the kit.

Sources

• Reddit — “What’s the most underrated way you’ve seen AI used for actual business tasks?” (r/artificial)
• ChatGPT
• Gemini
• NotebookLM
• Gamma
• Make
• n8n
• Telegram
• Tailscale
• PostHog
• LimyAI
• StoryPrism