You know how AI used to be something only tech companies talked about? Well, those days are over. Now, everyone from manufacturers to healthcare providers is jumping on the AI bandwagon. Every company including yours need to scale AI. But the question remains, how do you incorporate AI in your organisation? This is what we will explore in this article.
It’s no longer just about cutting costs or increasing profits for tech-savvy companies—it’s everywhere.
Back in June 2020, Gartner said that 75% of companies would go from just testing out AI to actually using it in their day-to-day operations. That prediction is coming true, but here’s the kicker: scaling AI isn’t easy.
To get the most out of AI, businesses need to implement it on a big scale. This isn’t just throwing a few AI models like GPT, LLaMa 3.5, Gemini, or even GROK into play. You’ve got to weave it into the entire fabric of the business—products, services, and how everything runs. When companies manage to do that, they can cut costs by automating boring tasks, improve how decisions are made, and find new ways to make money.
But here’s the catch: getting AI to that point is tough. Rolling out one or two AI models is a whole different ball game than using AI across the entire business. As companies push AI further, things start getting complicated. The more you rely on AI, the bigger the challenges become.
So, how can you actually integrate or scale AI in your organisation? Let’s dive into what that looks like, and how to do it.
What Does “Scaling AI in Your Organisation” Even Mean?
When we talk about scaling AI, it’s not just about testing a few models here and there. We’re talking about integrating AI deeply across the whole business. That means using it not just for one-off tasks but embedding it into daily operations, decision-making, and even how you interact with customers.
To really scale AI, it needs to be:
- Everywhere: AI isn’t stuck in one department. It’s in finance, marketing, customer service, and supply chain management, education—all of it.
- Consistent: AI needs to give the same level of insights and actions across the board. No silos.
- Sustainable: It’s not enough to just set AI up; you’ve got to maintain and improve it over time.
- Impactful: You’ll know AI is working when you see real improvements—whether that’s in efficiency, customer experience, or new ways to make money.
The Big Four: Data, Technology, Processes, and People
To scale AI, you need a plan that covers everything: data, tech, processes, and people. It’s all connected, so if one piece is off, the whole thing could fall apart.
1. Data
AI runs on data, so you need good data—lots of it, and fast. Make sure your data is clean, organized, and accessible across the company. For that, you will need people who are good with Data Analytics. If you don’t have some resources already, I would recommend Upskilling a few on Data Analytics skills.
2. Technology
You need strong tech behind your AI efforts, like cloud platforms, machine learning tools, LLMs (Large Language Models), and security systems. Plus, it needs to grow as your AI initiatives expand.
3. Processes
Your business processes need to adapt. Think automation for repetitive tasks and AI-powered decision-making baked into your workflows.
4. People
It’s not all about the tech. You need people who know how to use AI—data scientists, engineers, and AI specialists. Plus, everyone needs to get on board with AI, which means training and upskilling are key.
Strong Data Infrastructure = AI Success
If you want AI to scale, you need a solid foundation. That starts with your data infrastructure. It’s not just about collecting and managing data—it’s about building systems that can handle huge amounts of data without breaking a sweat.
You also need a smooth data pipeline. That’s the system that moves data from where it’s collected to where it’s analyzed. You want it to run automatically, with as little human involvement as possible, to keep things efficient.
Making a Plan to Scale AI in Your Organisation
Scaling AI isn’t something you just do on a whim. You need a strategy that aligns with your business goals. Start by asking yourself, “What do we actually want AI to do for us?” Make sure the projects you choose are directly connected to your company’s big-picture plans.
From there:
- Identify the business goals you want AI to support.
- Get stakeholders on board—business leaders, IT, end-users. Everyone needs to be on the same page.
- Set clear metrics so you know if your AI projects are actually working.
Focus on projects that are likely to succeed. Start small, score some wins, and use that momentum to tackle bigger AI challenges.
AI Isn’t a Solo Project: Get Everyone Involved
Scaling AI means getting multiple departments to work together. The more people you have from different parts of the business, the better your AI solutions will be. Collaboration means AI solutions that are better aligned with actual business needs and more likely to succeed.
MLOps: Keeping Your AI Running Smoothly
Once you’ve got AI models running, you need to keep them running smoothly. That’s where MLOps (machine learning operations) comes in. It helps streamline deployment, so your AI models can be updated and tweaked as needed without tons of manual work.
Plus, MLOps helps monitor how well AI models are performing. It spots when things start to drift (like when the model’s predictions get less accurate), so you can fix it before it affects business.
Training Your Team: The Key to Scaling AI
To make AI work, your team needs the skills to manage and use it. Upskilling and reskilling are crucial. Everyone from data scientists to non-technical employees needs to be comfortable working with AI tools. This not only impacts productivity but also helps create a culture that inclusive for innovation.
Overcoming Challenges in Scaling AI
Let’s be real: scaling AI comes with its fair share of challenges, especially around data quality and security. The more data you use, the bigger the risks. You need strong data management strategies to keep everything running smoothly.
There’s also the challenge of getting people on board. A lot of employees worry about AI taking their jobs. To ease these fears, businesses need to make AI adoption a team effort, with plenty of training and clear communication.
AI in Your Organisation: Wrapping It Up
Scaling AI is no easy feat, but if done right, it can transform your business. It’s about more than just having the latest tech—it’s about aligning AI with your company’s goals, building the right infrastructure, and getting your people on board. If you can pull that off, AI can take your business to the next level.