Undoubtedly, implementing AI into an existing company is a huge challenge. While adopting AI can significantly streamline work and accelerate many processes, the transformation process itself can be complicated and time-consuming. In this post, we want to show you three major stages of AI transformation. We hope this knowledge will help you with this process in your business.
According to IBM’s Global AI Adoption Index 2022, AI adoption continues at a stable pace in 2022, with more than a third of companies (35%) reporting the use of AI in their business, which is a four-point increase from 2021. Interestingly, the two countries with the highest AI adoption are China and India:
Still, more companies are exploring potential AI capabilities than implementing them. That’s because, for many businesses, it’s still a novelty, and AI adoption constitutes a big shift in the way your company works, which, obviously, takes time and effort.
Generally speaking, the process of adopting AI can be divided into three major stages. Let’s have a look at them.
Stage 1: Understanding
According to the state of marketing and sales AI 2022 report published by Drift and Marketing AI institute, this is where the majority of companies are right now:
In 2023, thousands of companies still don’t understand or want to implement AI in their everyday operations. That said, this stage is crucial. Without some degree of openness and flexibility, you won’t be able to make the most of AI.
At this stage, it’s essential to find answers to two questions:
What can AI be used for in our business?
Are there ready-made tools for such applications?
The first question requires some research. Currently, there are thousands of AI-powered tools out there. Many of them don’t even require advanced IT processes and can be implemented via simple API-based integrations.
According to cited IBM’s report, companies decide to implement AI-based solutions mostly because of the following questions:
43%: Advancements in AI that make it more accessible
42%: Need to reduce costs and automate key processes
37%: Increasing amount of AI embedded into standard off-the-shelf business applications
31%: Competitive pressure
31%: Demands due to the COVID-19 pandemic
25%: Pressure from consumers
23%: Directives from leadership
22%: Company culture
22%: Labor or skills shortages
20%: Environmental pressures
Do you identify with any of these reasons? If so, AI is probably a good solution for your business. At the same time, 34% of respondents mention limited AI skills, expertise, or knowledge as the main problem hindering successful AI adoption. There’s no way around it; if you want to adopt AI into your company, you need to do some digging and find the solution that’s tailored to your company’s capabilities and profile.
Stage 2: Piloting
36% of surveyed companies are at this stage. Piloting AI means implementing first projects and tools on a limited scale, just to see what’s what and how it works. At this stage, companies usually define some quick-win goals and narrowed-down use cases to see if AI is worth any further investments.
Such a narrowed-down goal can be to optimize prices in your online store. Today, many dynamic pricing tools use AI to make them more effective. Implementing such a tool is usually hassle-free from the IT perspective and enables you to see the first results in a matter of days, maybe two or three weeks, not months.
When we go back to IBM’s report, we see that the majority of surveyed companies use AI to deal with similar easy-to-measure and quick-to-solve problems, such as the reduction of repetitive tasks or facilitation of employee training:
Typically, it’s best to start with one or two AI-fueled tools and see how they work. Give yourself a few weeks or maybe months to conduct the necessary trials and estimate the first results. If you see the real impact of AI on the way your company operates, this means you can move to the third stage of AI adoption.
Stage 3: Scaling
Undoubtedly, this stage is the biggest challenge for most companies, as this is where the real transition happens. Only 15% of analyzed companies are at this stage, report Drift and Marketing AI institute in their study.
Scaling means AI is becoming an integral part of the majority (if not all) of your company’s operations. What does it mean in practice?
You use AI to analyze available market and company data to make more informed decisions.
Your marketing department uses AI to streamline work and make their campaigns more effective.
Your HR team uses chatbots to talk to potential candidates, and there is an AI-powered resume scanning tool so that your recruiters don’t have to spend hours sifting through hundreds of received resumes.
Your financial department uses fraud detection tools to spot any suspicious financial operations (e.g., orders from fake accounts).
Finally, AI-based automation tools enable you to automate the majority of repetitive tasks, such as sending welcome and order summary emails or reaching out to every user of your website who might be interested in your services.
As you can see, reaching this stage means that AI affects the whole company. Getting here surely takes some time and effort. But once you get there and your company becomes empowered with AI, everything becomes easier, faster, and more effective. And that’s worth every effort, isn’t it?
Wrapping up
Suppose you’re at the very beginning of your AI journey. There are no AI-powered tools in your company; you’ve heard something about it and are considering looking closer into it. What’s the best approach that won’t leave you overwhelmed? Start small. Consult your team, and select one or two areas of everyday work that take a lot of time and mundane work. It can be pretty much anything, e.g., sending emails or updating prices/product descriptions in your online store. The goal is to grab some low-hanging fruit and see the first results.
The next step is to look for available AI tools that can help you with your issue. Many of them are available in the SaaS model, which means there’s no need to rebuild your IT infrastructure or buy expensive software.
If you find a tool that seems reasonable and useful, opt for a free trial or a demo (90% of these tools enable some sort of non-binding test) and ask your team (or at least one or two employees working in the same area) to get acquainted with this tool, and conduct some tests.
If the results are promising, you can make this tool an integral part of your work. And then, you move to the next tool! Step by step, you will be able to implement several AI-powered tools. Just remember not to overcomplicate things. Treat AI as a way of making your work faster and easier. This way, you will be able to make the most of it without feeling overwhelmed by this technology.
