Skip Automation Hell: 3 Augmented AI Boosts To Get Fast ROI

It happened again.

Another enterprise, another million wasted. This time, on document processing (once more – sigh). AI was supposed to "harness all data – PDFs, images, emails, spreadsheets, slides" to "extract insights with highest accuracy" and (drumroll) – automation!" That was the vendor pitch.

Two years later, the vendor got kicked out and all that's left is a nice PPT deck, plus a few more thousands to clean up the mess. What went wrong? They trusted in AI too much and built their automation death star.

But turns out, you can't "AI" your way out of complexity. What you can do though is to augment your way through it. Delivering tangible results along the way.

Today, I'm sharing 3 practical patterns which you can implement today..

Let’s dive in!

When is an AI solution actually “successful”?

If you've been following my work, you know my answer: An AI solution is successful when it hits my 10K Rule – saving or generating $10K+ recurring per month, quarter, or year.

The mistake many AI teams make when starting out is that they design a project that couldn't be profitable until the very end. Two years of investment before seeing a dime of return.

It's a typical trap: Full automation forces you through the entire development cycle before you see any benefit. Best case, you automate entire business expenses away. Worst case, you shift expenses from doing the work to maintaining the automation. Guess which is more common.

That's why most "ambitious" AI initiatives fail. They can't deliver incremental wins.

To avoid this, I use AI Profit Roadmaps that break big goals into profitable steps. Each milestone delivers something valuable on its own. If you stopped today, you'd still have a net win.

You can't do this when you start with full automation.

But you can with smart augmentation.

Let’s see how!

3 AI Boosts To Skip Automation Hell

When you do effective AI workflow augmentation, are three core patterns I typically fall back to in order to hit a 10K threshold quickly (<90 days) and skip AI automation hell (almost) entirely. These "AI Boosts" are small, but powerful improvements embedded in existing workflows – allowing you to significantly enhance business performance without needing to rebuild entire systems.

Let's walk through them to see how they work, look at a few examples and how you can use them as a shortcut to $10K profit.

1. Decision Boosts

AI doesn't need to make decisions for you. It just needs to make your decisions better by pushing the right signal to the right person at the right time.

Examples:

• Prioritize the top 10% leads in your CRM

• Triage support tickets to route urgent issues faster

• Detect churn risk to prioritize which accounts need human touch

How it's typically done: AI classification → ranking → trigger the right human action. Feed past decisions into the model, then use scores to guide focus – not replace it.

Shortcut to 10K: Just one saved customer or closed deal can pay for the entire boost. Sales stops wasting time on dead leads. Support solves real fires before they spread.

2. Knowledge Boosts

Knowledge Boosts eliminate the gap between needing information and having it offered to them. This eliminates prep time, allows faster responses, and often enhances the quality of work, too.

Examples:

• Instant meeting summaries with action items

• Auto-generated customer briefs before sales calls

• Context-aware copilots that show relevant policies from your internal wiki

How it's typically done: RAG system → structured prompts → delivery anywhere you can call an API or have access to an AI chatbot. Think internal search that actually understands what you're asking for.

Shortcut to 10K: Have 5 people save 2 hours a week = 520 reclaimed hours/year = $50K+ back in reclaimed productivity. Shift focus on what to do with these hours, not how to get them back.

3. Output Boosts

Output boosters improve, repackage, or extend work that's already happening, making your team look 5x bigger without actually hiring. These typically touch high-volume, final-mile work and drive ROI by either lower cost per unit or more units shipped.

Examples:

• Turn a webinar into 10 posts, 1 article, and 2 emails

• Auto-rewrite internal docs into client-facing slides

• Turn messy data formats into clean reports

How it's typically done: Prompt chains → templates → human review in order to extract data from any (unstructured) source, transform it and then clean the result. Stack small steps into production-ready results.

Shortcut to 10K: Triple your output with the same team. Have one task feed five downstream channels. Or cut production time by 60%. Either way, you hit the profit line fast.

For none of these boosts you’ll need a highly integrated, highly automated AI solution. Simple assistants or copilots get you started fast.

Back to the Document Processing Example

Instead of spending a 7-figure budget on a fully automated AI document management platform, the team could have implemented any of these three boosters in less than 90 days with under $100K up-front investment:

Decision Boost: Have AI pre-sort documents by complexity – routing simple documents straight through, flagging complex cases for human review.
→ Estimate: 10-30% fewer manual cases

Knowledge Booster: For tough cases, have AI pull in context from past resolutions on demand. Show how similar cases were solved before.
→ Estimate: Have tough cases resolved 2x faster with higher quality

Output Booster: Reviewers type notes in plain text – AI fills the formal form.
→ Estimate: 10-20% faster processing due to easier entry and less form-fatigue

Which of these is an AI moonshot that excites shareholders and CEOs?
None.

Which of these can result in fast, tangible ROI?
All.

Each of these could stand on its own and deliver immediate value. Or you could build a roadmap that connects the dots and transformed the entire document processing workflow without starting to rebuild the entire system.

When to Boost vs. When to Wait

Not every process can be boosted with AI augmentation yet. Here's how to spot the difference:

Start with AI Boosts when:

• ✅ The workflow already works, just slowly or costly

• ✅ You can measure the current cost of delays/errors

• ✅ You have examples of good vs. bad outcomes

Skip AI augmentation (for now) when:

• ❌ The process is undefined or constantly changing

• ❌ There’s no business impact when improving the workflow

• ❌ There’s AI resistance in the team – get them onboard first

Build Bridges, Not Rockets

Instead of trying to build rockets to the moon, try building bridges to better decisions, faster insights, and higher-quality outputs. And make it profitable along the way. Most of your best ROI lives one layer above your current process – not ten layers away in some distant automated future.

Ironically, the three AI Boosts can be your ladder to full automation. Because once you know what works, it’s much easier to hand it off to a system that’s running on autopilot. But tackle the ladder step by step.

Want to see these Boosts in action?

I just ran a live workshop called Dead List to Dollars, where we took a raw list of B2B contacts and turned it into rich, sales-ready leads — using exactly the kind of AI Boosts I talked about above:

• 🧠 Knowledge Boost to research company info

• 🧭 Decision Boost to prioritize leads based on deal size and buyer role

The full recording is available until Sunday before it goes behind closed doors. It’s hands-on, fast-paced, and shows how these boosts work in the real world.

👉 Watch how these Boosts work — before doors close Sunday

Your next step: 

Look at your team's biggest time sink last month.
Which of the AI Boosts above could have helped? How?

Start building bridges.

See you next Friday!
Tobias