A report compiled earlier in 2024 highlights a notable gap: while over 95% of companies are planning for artificial intelligence, only 20% are prepared to start adopting it. This discrepancy underscores the complexity of AI integration and that this process cannot be tackled easily.
So, in this article, I would like to explore some of the critical mistakes I believe companies can make when assessing how ready they are for AI.
Waiting for a “Better” time
Many companies out there are waiting for AI technology to grow more mature or for universal solutions to emerge to ease the integration. They hope to see industry-wide adoption and standardised options before committing.
However, I, for one, believe that this is a mistake, one that can lead to competitive disadvantages. While you wait, you risk letting more proactive competitors gain ground on you by developing and implementing their own AI solutions, gaining valuable experience and market advantages in the process.
The same issue can be raised when we look at the level of AI-related education. As things stand, the rapid evolution of this technology outpaces the development of specialised educational programs. This leads to a shortage of skilled professionals, which means that companies either have to compete fiercely over them or train their own personnel internally. Companies that intend to wait for the educational landscape to catch up are all too likely to find themselves left behind.
Underestimating the cost and profitability of implementation
Another critical mistake is failing to properly consider the costs associated with AI integration and overestimating what it can do for your business. The main goal of integrating AI is to enhance operations and boost profitability, but this requires a careful cost-benefit analysis.
Before committing any serious resources, a business must evaluate the required compute power and the AI's capability to perform the tasks intended for it. This evaluation should help you figure out whether implementing artificial intelligence will, in fact, lead to significant cost savings and greater operational efficiency.
If the answer you get is not a definitive "yes," then it is entirely possible that your business does not actually need AI to perform its functions. And there is no need to forcefully adopt it just to ‘keep up with latest fashion’. It is certainly much better than investing in technology that does not deliver substantial improvements.
Take the early adoption of 3D televisions, for example. The initial excitement when the tech first appeared led to widespread purchases, but since then the technology failed to prove its long-term value. And as a result, practically no one uses them these days.
Lacking a clear focus on AI utilisation
This partially ties in with my previous point – there is no sense in adopting AI if you cannot perceive any notable benefits that could come from it.
It is not unusual for companies to lack a clear understanding of which parts of their operations to upgrade through AI. Use cases that are too big run the risk of creating doubts among employees if they fail. On the other hand, if the use case is too minor, it might not get enough momentum and support either.
This uncertainty and absence of prioritisation play a big part in slowing down the adoption process. Workplace surveys indicate that 42% of employees believe their companies lack a clear idea of which functions to automate using AI.
To my mind, the most impactful applications lie in automating routine tasks such as customer support, account management, and basic compliance in financial services. And while focusing on optimising internal processes with AI may not be as immediately profitable as the client-facing services, it can still yield substantial benefits.
Take Google's AI Teammate, for example. It is designed to sort through the company's documents and emails, easily finding necessary information, analyzing it and offering ideas. All of these functions serve to streamline internal operations and help teams better perform their work. Greater efficiency means faster results; faster results mean greater customer satisfaction and loyalty, allowing for stable profits in the long term.
Ignoring current and future industry regulations
AI integration demands careful consideration of not just technological and financial factors, but of compliance as well. This industry is still new, and, as such, it is subject to great regulatory scrutiny. New rules are being considered, adopted and discarded all the time, and it is hard to predict how the situation may change even months from now.
Not only that, but different countries have varying standards and timelines for AI implementation. So companies that seek to operate internationally have to take into account a whole plethora of interchangeable rules. This can pose a significant challenge, and failure to comply with regulatory demands can not only hinder your efforts in AI adoption, but also lead to steep fines and reputational damage.
Final thoughts
If you want to put together an AI adoption strategy that promises success, your approach has to be proactive and flexible enough to anticipate future developments. You should not wait for ready-made solutions but instead invest in developing tailored AI applications that would work best for your business.
When your investments have yielded significant improvements in operations and profitability, when the automation of fundamental functions has ensured that your employees can focus on more complex tasks – that’s when 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.
