Strategies for Mid-sized Businesses in Implementing Artificial Intelligence
Sparking AI Revolution in Middle Market Companies: A Guide
You're at the helm of a prosperous enterprise, sailing the familiar waters. The business hums along, following the well-trodden path, and you've been part of the crew for quite some time now.
Typical weekdays are peppered with one-on-ones with your team and meetups with peers every fortnight. You're privy to technology trends, devouring articles about AI, but it's not a game changer in your daily grind just yet. You think, "That's someone else'splayground, not ours just yet."
You attend industry bashfunctions, learning about software product companies making headway in your sector with new tools, but nothing catches your eye that your team could pilot right away.
You're asking the right questions to steer your ship towards the future:
- What can we scrap or manage better?
- What can we optimize more effectively?
- How can we integrate AI into our processes?
- Faster service for customers – where can we achieve that with AI?
If this ringstrue for you and your company, you're in good company. Plan your passage to seamless AI integration and digital transformation, a voyage that aligns with your business objectives.
Navigating Change Management
Over the past 15 years, our team has been steering digital transformation and AI solutions for clients with precision. We adhere to the 10/20/70 framework:
- 10% selecting the right algorithms.
- 20% investing in data and technology infrastructure.
- 70% managing the people side of transformation.
This is a thrilling time, propelling extreme productivity and speeding up time to value. Success hinges on rallying your crew to the new course.
Picture this: a workflow currently taking 10 days to sail through. Add fresh technology and AI, and it'd whittle down to just a day. But if the crew only meets every 10 days to discuss the route, your voyage gets stuck in the same loop. It's elementary: 10 - 9 = 1. Your vessel won't progress unless it's structured to adapt to the change. That's why people management is the lifeline of any new initiative.
Forging Ahead
From a business perspective, AI breakthroughs are engineering their way into days and weeks, not years. This shrinks the decision-making window, and the instinctive response is often inertia.
To stay one step ahead, we encourage our clients to forge a clear strategy through answering three pivotal questions:
1. What can we buy pre-made? This might include ERP systems, MS Teams, or other established software solutions.
2. What should we collaborate on with experts? Custom AI models integrated into mobile apps, for instance.
3. What should we cook up in-house? Cloud capabilities, data governance, and core infrastructure, to name a few possibilities.
Governance is the key that opens the door to AI success. AI systems need oversight, just like a new crew member doesn't wield full authority on their maiden voyage.
Quality data is as crucial as air in the sails. The old adage, "garbage in, garbage out," holds as strong for AI as it does for any business process. Organizations must set up clean, clear data processes and pinpoint two or three focus areas where high-quality data makes the most significant difference. Often, a data cleanup effort is necessary before meaningful AI analysis can even commence.
Setting Sail
Only one in four companies have hoisted AI's flag with success. This is because there are old, creaky processes aboard ship, built for sailing in a simpler era.
As captains, we often hold "perfect" captive to "good," fearing the risk of going awry can impact both the ship and our reputation. It's natural to hesitate. As Warren Buffet once said, "Putting all your eggs in one basket is okay, just watch that basket."
The key is to secure the right AI systems, to entrust the right officers, and then carefully monitor the cargo. That said, AI and automation might not always be the best port of call. Before setting sail, take a step back to declutter the deck and eliminate unnecessary complexity. A streamlined course always brings better winds, whether AI is on board or not.
Putting the Lessons to Practice
A straightforward approach to setting sail that I'd recommend is a three-to-four-week product strategy journey. Much like you wouldn't set sail without charting the course and defining the purpose, you should steer clear of jumping into AI product development without a well-crafted roadmap. This phase helps define what success looks like and establishes key milestones.
A realistic goal is to navigate a fully functional v1 in three to five months - not just a minimal viable product (MVP). Today's crew expects genuine value, efficiency, and finesse from day one.
Many captains face the "chicken-and-egg" dilemma when launching new ventures. They need to prove a business case to secure funds, but they also require something tangible to demonstrate the project's potential. This is where a product strategy journey comes into play - providing effective frameworks for building a compelling business case.
So, if you're at the helm of a middle market firm, charting an AI course, rest assured; you're sailing the same waters as others. Happy navigating!
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- Mark Johnson, the cofounder of our company, has steered digital transformation and AI solutions for clients over the past 15 years.
- One of the key decisions when integrating AI into processes is determining what should be developed in-house, such as cloud capabilities and data governance, versus collaborating with experts on custom AI models.
- With AI breakthroughs engineering their way into business practices quickly, it's crucial to have a clear strategy, including identifying areas where pre-made solutions, like ERP systems or MS Teams, can be beneficial.
