Future-Proofing Enterprises with Tailored AI Strategy Consulting

A couple of days ago, we were at a dinner, and one of the guests was a camera operator for a well-known Argentinian TV production company. The man worked elbow to elbow with the brass. So, we got to talking, and – as an AI strategy consulting firm – we had to ask him: “How are you using AI in your series? And soap operas?” 

Answer? They weren’t. They simply didn’t know – the company as a whole – what the big issue was with AI content creation. They simply didn’t know how the tech could be used in-house by them. We were floored. Mind you, this was one of Argentina’s biggest television production companies and most execs weren’t even tinkering with the possibility of AI. Keep that in mind cause we’re going to round it up at the end. 

The Pressure to Keep Up with Rapid Tech Evolution

Technology never slows down. It never takes a breather. In a week, it will make gigantic leaps, and a week after, it will leave those jumps in the dust.  Businesses battle it out in an arena with a myriad of ongoing death traps— slice-and-dice feats like managing massive data sets, keeping up with shifting customer expectations, fixing operational inefficiencies, and trying to juggle what’s the best tool available. The numbers tell the story – and the story is a Grimm Fairytale gone mad.  According to McKinsey, companies that use AI for making decisions, for example, see a 20-25% increase in profitability. Still, many businesses don’t even know how to implement AI correctly. 

In a 2023 Deloitte survey, only 27% of enterprises reported successfully deploying AI at scale. Retail is a prime example. Large e-commerce platforms use AI-powered recommendations, automated supply chains, and predictive analytics to stay ahead. Meanwhile, smaller retailers without a structured AI strategy struggle to keep up. Healthcare faces similar pitfalls. AI-driven diagnostics can detect diseases earlier and improve patient outcomes, but without the right implementation, hospitals risk investing in solutions that don’t integrate with existing workflows. This is why AI strategy consulting is essential. Instead of vague digital transformation goals, companies get a bespoke roadmap designed to solve their specific challenges.

How Tailored AI Strategy Consulting Future-Proofs Enterprises

Aligning AI with Business Goals

AI is a tool, not a solution by itself – and even that, according to some futurists, isn’t right. AI, they’ll tell you, is an agent – not a tool. It’s the equivalent of having a hammer that can decide when to strike the nail, at what angle and what force, and while it’s at it, tell you how to properly build your house – and do your taxes. 

Without a clear strategy, companies waste money on projects that don’t sync with their business goals.

A strong enterprise AI strategy starts with answering key questions:

• What problem needs solving?
• How will AI support business goals?
• What metrics will define success?

Coca-Cola offers a great example of what to do. Instead of adopting AI just because it was trending, the company used AI-driven analytics to improve supply chain efficiency and predict product demand. The result? Lower operational costs and higher profit margins.

Building a Scalable Enterprise AI Strategy

One of the biggest mistakes companies make? Implementing AI in a way that doesn’t scale. Many launch AI projects that work in isolation but collapse when expanded across departments.

A well-designed AI strategy makes sure long-term goals are met — and really it’s used as a launching pad.. Netflix mastered this approach. The company initially applied AI to improve content recommendations. Once that model proved effective, they expanded AI usage into production scheduling, server load balancing, and streaming quality adjustments based on network conditions.

The key? A structured, adaptable, easy-to-build-up and scale strategy—not a fragmented, labyrinthine approach that leads to hiccups and thousands of lost hours.

Maximizing ROI with Targeted AI Applications

AI projects can become expensive fast – really expensive. Companies need to focus on high-impact applications that deliver great returns. They need to think not just about the woods or forest but about the trees – they need to think in the short term – what we can do today – and in the long term – what we can do tomorrow. 

For instance, JPMorgan Chase uses AI to detect fraud, saving the company millions by identifying suspicious transactions in real-time. Instead of applying AI across all transactions, they focus on high-risk cases, increasing its punch without overloading systems.

Businesses that randomly integrate AI often fail. AI must generate voracious insights that drive actual business results—not just exist for the sake of “innovation.”

Enhancing Data-Driven Decision-Making

AI thrives on high-quality data. Poorly structured data leads to flawed predictions, wasted resources, and unreliable business decisions. AI is just as good as the system it is built on the data sets that teach it. For example, you might have a bright – high-IQ – kid, but unless you curate his passions, educate his academic endeavors, and feed him the right data, all that potential will be lost. There is a fine line between nature and nurture, and the former can only take you so far.

Spotify provides a great case study. Its recommendation engine doesn’t just analyze what songs users listen to—it considers the following:

• Listening habits (time of day, frequency)
• Song skips and replays
• Playlist creation trends

By refining this model continuously, Spotify creates mellifluous listening experiences that feel personalized. The result? An 80% increase in user engagement from AI-powered recommendations.

Mitigating AI Risks and Ensuring Compliance

AI isn’t risk-free. Bias in algorithms, security vulnerabilities, and regulatory concerns can create serious business and legal hurdles.

Take the hiring industry. Some AI-driven recruitment tools have been found to favor certain demographics due to biased training data. Amazon scrapped its AI hiring system after discovering gender bias in its recommendations.

Bias is a huge issue when it comes to AI – why? Because there’s a reason why they are called machine learning algorithms – they need to be taught. And who’s teaching them? We mortals and flawed creatures. In most cases, our biases aren’t as plain to see as we would like them to believe. For example, Midjourney is now allowing each user to train their profile and create a personalized style profile. 

A study found that after 2000 data sets – users having to choose between photo A and photo B – the platform ended up developing a psychological profile much more exacting than anything an actual shrink could think of. After 5000? Or 10000? Just imagine. And each image is picked rapidly and without much forethought – but each subconscious decision tells the platform – and the algorithm – something more about us, something we didn’t even recognize. 

To avoid these issues, businesses must integrate compliance checks into their AI strategy from the start. Responsible AI implementation isn’t optional—it’s a necessity.

Long-Term Value of a Tailored AI Strategy

AI isn’t a one-time project. Companies that treat AI as a panacea—a cure-all for their inefficiencies—set themselves for a reality check that will leave them feeling like Neo after taking that dabble pill. Monitoring, optimization, and adaptation – those are the keys to long-term success.

According to PwC, AI will contribute $15.7 trillion to the global economy by 2030. However, only businesses with a structured, evolving enterprise AI strategy will reap the benefits.

What’s Next? Stay Ahead or Fall Behind

AI isn’t the future—it’s the present. Companies that build a bespoke AI strategy will lead their industries. Those that hesitate will lose market share.

Now, back to the TV production company. What happened? Well, we showed them a rather famous commercial in Argentina that had been produced about 10 years ago for a telecommunication company. It was a baby talking to his parents. Simple, sweet, and fun. What was the cost of that commercial back when it was created? Over $280 thousand. They needed to develop the special effects so that the baby wouldn’t sink into Uncanny Valley territory. Today, anyone with a computer and the right app – let’s say Kling or Runway – could do that same FX and commercial for the cost of a Big Mac.

The choice is clear. Where does your company stand?