top of page
  • Writer's pictureCJAZ Consulting

Guide to Understand the Risks and Limitations of Artificial Intelligence in Business

As a small business owner in London, in our last blog we looked at the benefits of leveraging artificial intelligence (AI) for your business, such as improved productivity, profitability and business results. However, before you jump into implementing AI, it's also important to understand the limitations and risks associated with this technology.

Limitations of Artificial Intelligence

Availability of Data

One of the main barriers to implementing AI is the availability of data. Data is often siloed or inconsistent and of poor quality, which presents challenges for businesses looking to create value from AI at scale. To overcome this, you should have a clear strategy from the outset for sourcing the data that your AI will require.

Skills Shortage

Another key roadblock to AI adoption is the skills shortage and the availability of technical staff with the experience and training necessary to effectively deploy and operate AI solutions. Research suggests experienced data scientists are in short supply, as are other specialised data professionals skilled in machine learning, training good models, etc.


Procuring AI technologies can be expensive, especially for businesses that lack in-house skills or are unfamiliar with AI and have to outsource. The computational cost for training data models can also be an additional expense.

Upgrades and Maintenance

Software programs need regular upgrading to adapt to the changing business environment and, in case of breakdown, present a risk of losing code or important data. Restoring this is often time-consuming and costly. However, these risks can be mitigated provided that the system is designed well and those procuring AI understand their requirements and options.

Other AI limitations relate to implementation times, integration challenges, lack of understanding of the state-of-the-art systems, usability, and interoperability with other systems and platforms.

Considerations for AI-Driven Technology

Customer Privacy

AI raises concerns over customer privacy, especially as data collection becomes more extensive. It's important to ensure that you comply with relevant data privacy laws.

Lack of Transparency

As AI systems become more complex, it may become difficult to understand how they make decisions. It's important to ensure that AI systems are transparent and explainable.

Technological Complexity

AI systems are complex and require technical expertise to operate. It's important to ensure that you have the necessary technical skills or have access to experts who can provide support.

Ethical Concerns

As AI rapidly develops, several ethical issues have been raised, including:

  • Job Losses Automation technology has the potential to give rise to job losses, and it's important to consider the impact on employees.

  • Distribution of Wealth There is a need to ensure that wealth created by machines is fairly distributed.

  • Algorithmic Bias Bias in the data can result in algorithmic bias, which can unfairly impact certain groups of people.

  • Security There is a need to ensure the security of AI systems, especially those that can potentially cause damage.

  • Unintended Consequences Smart machines are thought to learn and develop independently, and there is a need to mitigate against unintended consequences.

While there are risks and limitations associated with AI, if implemented responsibly, it has immense and beneficial potential to create better business and better lives for everyone. If you're considering AI-driven technology, it's important to carefully weigh the benefits and risks and seek help from experts when needed.

As an experienced MSP, we have helped many of our clients adopt advanced technologies to help them work smarter. We are always here to talk through business benefits and any foreseeable disadvantages to using your considered tech – just give us a call 020 3950 0360


bottom of page