The report, compiled in early 2024, highlights a notable gap: while over 95% of companies plan to adopt artificial intelligence, only 20% are ready to actually begin their implementation. This discrepancy highlights the complexity of AI integration and that this process is not something to be taken lightly.
So in this article, I want to highlight some of the biggest mistakes companies make when assessing their AI readiness.
Waiting for “Better” Times
Many companies are waiting for AI technology to become more mature or for a general-purpose solution to make integration easier, hoping to see industry-wide adoption and standardized options before making a decision to deploy it.
However, I personally believe this is a mistake and can lead to a competitive disadvantage: while you wait, you risk that more aggressive competitors will catch up with you by developing and implementing their own AI solutions, gaining valuable experience and market advantages in the process.
The same problem emerges when we look at the level of AI-related education. Currently, the rapid evolution of this technology is outpacing the development of specialized education programs. The result is a shortage of skilled professionals, and companies must either compete fiercely for them or develop the talent in-house. Companies that wait for the education environment to catch up will likely be left behind.
Underestimating implementation costs and profitability
Another critical mistake is overestimating the impact of AI on your business without properly considering the costs associated with AI integration. The primary goal of AI integration is to enhance operations and increase profitability, which requires a careful cost-benefit analysis.
Before committing serious resources, businesses should assess the computing power they require and the ability of AI to perform the desired tasks. This assessment will help them determine whether implementing artificial intelligence will actually lead to significant cost savings and operational efficiency gains.
If the answer isn't a resounding “yes,” there's a good chance your business doesn't actually need AI to perform its functions, and there's no need to force-adopt it just to “keep up with the latest trends” — it's far better than investing in technology that won't bring you any real improvements.
Take for example the early adoption of 3D televisions: when the technology first came out, there was a lot of initial excitement and many people jumped on board to buy one, but since then the technology has failed to prove its long-term value, and as a result very few people have 3D televisions today.
Lack of clear focus on leveraging AI
This partially ties into something I said earlier: there's no point in adopting AI if you can't see any significant benefits from it.
It's not uncommon for companies to not have a clear understanding of which parts of their business should be upgraded with AI: if the use case is too big, it risks raising employee doubts if it fails, while if it's too small, it may not gain enough momentum and support.
This uncertainty and lack of prioritization are major factors slowing down the adoption process: according to a workplace survey, 42% of employees believe their company lacks a clear idea of which functions should be automated using AI.
In my opinion, the most impactful application will be automating mundane tasks like customer support, account management, and basic compliance in financial services. Focusing on optimizing internal processes with AI may not yield as immediate benefits as customer-facing services, but it can still have significant benefits.
Take Google's AI Teammate, for example. The tool is designed to organize your company's documents and emails, easily find and analyze the information you need, and suggest ideas. All of these features help streamline your internal operations and help your team get their work done more efficiently. More efficiency means faster results. Faster results mean more satisfied and loyal customers, which translates into more stable profits in the long term.
Ignoring current and future industry regulations
Integrating AI requires careful consideration not only of technical and financial factors, but also of compliance. Because the industry is still new, it is subject to intense regulatory scrutiny. New rules are constantly being considered, adopted, and repealed, and it's difficult to predict how things will change even in the next few months.
What's more, different countries have different standards and timelines for AI adoption, so companies looking to operate internationally must consider a multitude of compatible rules. This can be a major challenge, and failure to comply with regulatory requirements can not only hinder your AI adoption efforts, but also lead to costly fines and reputational damage.
lastly
If you want to develop a successful AI adoption strategy, you need an approach that is proactive and flexible enough to anticipate future developments. Instead of waiting for an off-the-shelf solution, you need to invest in developing customized AI applications that are best suited for your business.
When your investments produce significant improvements to your operations and profitability, automating basic functions and freeing your employees to focus on more complex tasks, you can confidently consider your AI strategy a success.
Roman Eloshvili is the founder of ComplyControl, a UK company specialising in cutting-edge technology solutions for banks.
