Practical AI: How to Choose the Right AI Solutions for Your Business
Opening: Where do I even start?
Artificial intelligence is a gigantic and constantly-evolving field, with tech breakthroughs and strong opinions filling our newsfeeds every day. But how do we - as business leaders whose valuable time is already spread thin - sort through it all? How do we find what our business *really* needs to know, and what solutions to integrate?
Here a few ways to help you hear through the AI noise and find the solutions that make sense for your business.
Step 1 - Don’t follow the hype
Trendy terms ≠ lasting value.
The very first thing I tell clients is: don’t try to keep up with the trends. I’ve been in the field for 10+ years and was studying natural language processing (the foundation of modern AI) before it became a hot topic. Over that time, I’ve seen one enduring pattern: tech companies constantly reinvent terminology—often not to describe something new, but to spark curiosity or attract investor attention.
So don’t stress about knowing the difference between a “chatbot” and an “agent.” That’s not what will move the needle for your business.
Next: no one can read or learn everything (and they don’t need to).
Even as an expert, it’s infeasible to keep up with the overwhelming flow of AI news, releases, research, and opinions. That’s likely true for you, too—and it’s okay. The real skill in this modern age isn’t keeping pace with everything; it’s identifying which pieces are worth your attention based on your business goals.
Hype cycles fade, and flashy demos don’t always translate to real-world utility. Synthesising what you need from the info stream is key, which also means learning when to turn the stream off.
I used to stay busy playing catch up—chasing every update, every release, every new paper. I felt like I was doing what was responsible and necessary for my team, staying thoroughly alert to the latest innovations. But all it really did was wear me out. As my list of links-to-read grew longer and longer, I realized I had lost the goal.
My objective as a business leader isn’t to track headlines, but to notice the deeper patterns and insights that help us get compelling results. Now, before I even start reading, I set a limit: maybe a time-based “I will only read for 15 minutes, 5 minutes on each of these articles”, or an outcome-focused goal like “gather the core takeaway: is there a change that affects my process positively (that will make my workflow smoother) or negatively (something that puts my business at risk)?”
Recently, I even built an automation to help: each week, it gathers the highlights on a topic (for example, natural language processing) from a few feeds over the previous week, synthesizes out the pieces I care about for my work (by asking my unique questions, considering my unique business goals), then turns it into a short audio to help me orient at the start of my week – a personal audio digest.
These few shifts help me leave plenty of room to synthesize what I’m hearing and reading. I’ve learned that, at a certain point, more input doesn’t equal more clarity — clarity comes from knowing when to stop, honoring the quiet space necessary for real insights to settle in.
Finally, keep in mind that the loudest voices often have an agenda.
We live in a time where you’ll hear strong recommendations from all directions—open-source champions, tech startups, academics, influencers. But every recommendation comes with its own assumptions and motivations. At Liberated Leaders, we always say “follow the incentives.”
An AI enthusiast might rave about a lightweight model you can run on your own server—but they won’t be there to troubleshoot when it breaks.
Meanwhile, a commercial solution might offer slightly less flexibility but comes pre-integrated, secure, and reliable for your non-technical team.
Choose based on fit, not flash.
Step 2 - Focus on your unique needs
When considering AI solutions, it’s vital to focus on your unique needs: the specific goals, challenges, and opportunities available to your business – including your team’s readiness to adopt different workflows.
First of all, what works for someone else won’t always work for you.
The biggest mistake I see? Teams implementing a tool or framework mainly because they heard it was the smart thing to do, from people with different goals, resources, or constraints. It’s critical to pause and ask:
What problem are we solving here - is that a priority for us right now?
Does this fit our workflow? Our team’s capacity? Our growth stage? Our resources?
What assumptions does this solution make, and do they hold true for our business? Do we have different constraints?
It’s also important to know that AI isn’t one-size-fits-all—sometimes, it’s not a fit at all.
AI isn’t magic dust. It’s powerful, but it also comes with tradeoffs. Sometimes, a simple tool or process change will do the job better than a fancy, cutting-edge system. For example:
If a task is highly repeatable and must be done the same way every time, a traditional, rules-based system or script might be the better fit.
If your systems rely on very consistent data formats, you may want to steer clear of generative AI unless you’ve validated its output stability. (It’s possible but requires extra time and expertise!)
But if a task requires more language fluidity, interpretation, or analysis, that’s a good signal for when to use a generative / LLM-powered system.
For example, your users might input something in a lot of different ways that are hard to predict, like how they will express a greeting: Hi, Hello, How are ya, What’s up, or jumping right into their need without a greeting at all!
For example, if you need to collect info about your customers and one constraint is you need it in a very strict format, reliably, it probably makes most sense to use a Google Form or similar – using OpenAI’s LLMs wouldn’t fit well here. And if you need to do mathematical operations on some numbers in your spreadsheet, do that with a spreadsheet function – again, not an LLM. Want to handle complex customer support interactions? A strict form is likely to frustrate your users when they can’t find the option for what they want to express, while a custom chatbot can understand them more smoothly, especially with an LLM integration.
The right tool should fit your goals and your constraints.
Lastly, match tools to your team’s reality.
Every business has different strengths. If your team isn’t made up of software engineers or data scientists, you don’t need to build complex systems from scratch.
Look for tools and framework that:
Integrate smoothly with what you already use
Don’t require steep learning curves for your team
Are easy for your team to adopt and maintain
This means asking questions like:
Where does my team communicate - on Slack, Teams, by email, phone?
Where do they collaborate - in Google Docs, sending .docx files around, Excel, Notion?
Where do they store data - a database, Google Drive?
Keep in mind that the best solution is one your team will actually use, because you’ve ensured it’s designed to be easy to interact with - one option is to ensure you have an expert AI consultant who can bridge the gap, integrating the automations with the tools your team already uses. When I consult with companies, my central goal is to lower their daily burden and task effort, and integrating with their existing tools - lowering the learning curve - is a key part of that. A solution that requires a large up-front learning effort from your team is likely to go unused.
Step 3 - Start with something small
You know the saying: perfectionism is the enemy of progress.
Many business leaders wait too long, holding out for the “perfect” solution. But useful automations are built iteratively. Start small. Something like:
Getting a notification text (summary, priority level) when a new lead comes in
Auto-organizing form responses into a spreadsheet
Another automation from our 9 examples below
These might seem minor (or maybe they seem intimidating)—but they free up real and valuable time, create momentum, and spark bigger ideas of how your team can work more smoothly.
Choose a low-friction, high-value first step.
Ask yourself: What’s one improvement we could adopt easily, right now?
There are many practical, lightweight automations that work great for small to mid-size businesses - to help businesses identify core areas where they can benefit from automations, I developed the Content Process Insight (CPI) framework, which consists of three main automation groups. Which one is a good fit for your team’s current needs, the tasks where they spend the majority of their time?
Content: Create social posts, draft emails, prep blog outlines
For example, draft responses to common emails (handling FAQ-like interactions: store hours, common problems, etc..) and store them in your drafts folder for easy review and sending
Process: Route information between tools, notify stakeholders, reduce copy-paste busywork, handle routine procedures automatically
For example, notify your team in Slack when a new order comes in, and auto-message the customer to confirm receipt
Insights: Summarize spreadsheets, track performance vs. goals, extract trends from customer feedback
For example, summarize your team’s weekly activity into a quick highlights email linked to your quarterly goals - and maybe send a bit of encouragement, highlighting a few of your team’s major wins for the week!
Here are 9 great ideas, automations we’ve built for multiple clients and which have delivered nearly-instant results - do any of them match pain points in your business’ daily tasks?
And the last step: include your team in the growth.
Once you’ve picked a small automation, it’s time to introduce it to the other people who will interact with it each day.
Let your team know what’s coming, why you chose it, and open space to discuss the goals of the automation: how will it benefit their day-to-day workflow? What metrics / KPIs are we using to evaluate if it’s working as intended?
Also remember that many of your team members may be (justifiably) concerned about automations replacing their role – my position is always to explore how AI can augment our daily tasks, allowing us to focus on what matters most rather than being weighed down with the manual tasks. In my teams, I am always aiming to enable everyone to contribute their unique expertise and focus their time on what really deserves their complex analytical skills - leaving the highly manual, repetitive tasks (that we rarely enjoy) to the computers.
Invite your team to reflect and share openly about their concerns & questions:
What might make this harder for them to adopt right now?
What risks do they see?
What support would help?
Also invite them to share what opportunities they see and what excites them - they will likely be excited when they realize how many repetitive steps or how much manual work this will remove from their daily tasks!
Start with a short trial period, then check in on how it’s going.
Remember that even the best tool will flop if your team isn’t ready for it—or doesn’t trust it. As a leader, you’ll need to understand why you believe this new solution makes sense for your team and be able to communicate it in tangible terms. Let them know you’re not just plugging in tech; you’re designing a better way of working. Make space for feedback, and adjust as needed.
Closing: Small steps = real wins
Though the constant stream of new innovations in AI can seem intimidating, you can make a small but impactful change today. It’s proven: leaders like you are already getting big results with small changes. When you choose an automation that fits your business and goals and that your team is ready to adopt, you will start to save your business significant time, money, and stress. Businesses of all sizes are finding huge savings, getting more done, and making better decisions with automations at key points in their processes.
Finding the right-fit improvements that make sense for your business' needs, using AI to uplift your team and streamline your operations, starts with one step at a time -- and can be especially smooth with a trusted, expert AI consultant at your side. Find experts who aren't motivated to just sell you the latest AI trend and who will study your business enough to make a careful, tailored recommendation.
Take a moment to review the 9 example use cases I highlighted above. Which of them could your team benefit from most right now? Your team - and future you - will thank you for taking a small step today.
About the Author
As a Success Artisan with Liberated Leaders, Ahn Michael leverages over a decade of expertise in Artificial Intelligence (AI) & Natural Language Processing (NLP), consulting with business leaders to scale their growth. They co-founded Equità Technologies, a premium automation agency streamlining manual processes, saving leaders’ valuable time & focus for key decision-making. Their approach blends technical rigor with strategic care – they prioritise understanding each business’ unique needs to deliver tailored, expert results.
Note: This blog was 90% human generated and 10% machine (AI) generated.
