8 challenges of artificial intelligence
Look around you – do you see any artificial intelligence? Many of us use this technology in our daily lives without even knowing it. You might use your virtual assistant during your morning ritual, use a navigation program to get to your first appointment and then do some shopping at lunch that provides you with personalized recommendations.
AI is just as common in business, from chatbots to inventory and supply chain management. As a business owner, you may know the benefits – but what are the challenges of artificial intelligence? Whether you plan to use AI to grow your business, improve efficiencies or build customer relationships, you need to know these top artificial intelligence problems.
1. Knowledge
Most people have heard of artificial intelligence through the news, movies and media. Yet truly understanding artificial intelligence issues requires a specialized knowledge of how it works, including how to write algorithms, roll out deployment and continue to refine it. Innovating new applications for AI and advancing the field requires even more knowledge.
The field of AI is still relatively new, and not many people have this specialized knowledge. This leads to a hesitancy to uptake new technologies like AI, but make no mistake: Business owners who lead the way in implementing AI will have an edge over the competition.
2. Skilled workers
Closely related to the AI problem of lack of knowledge is a lack of skilled workers. While over the long-term AI programs will make your life easier as a business owner, they do require some setup and sometimes have a learning curve.
Don’t let this deter you. There are plenty of AI applications that are relatively easy to set up, like chatbots to help you engage customers, digital voice assistants and automated reading and transcription. Other popular AI applications are cybersecurity, fraud prevention and payments processing, although these may require you to bring in an expert, at least temporarily.
3. Data
One of the biggest artificial intelligence problems is that it still leans heavily on human knowledge and skills – but it also needs data, and lots of it. Choosing the right set of quality data for an AI application helps it do its job better, faster and more accurately.
Organizations must make sure that their data is not biased – that is, based on a limited number of people who are too similar. Data must also be clean, as incomplete, inaccurate or corrupt data will weaken its accuracy. If you’re thinking about implementing AI in your business, do your research into where the vendor gets its data and how the data is maintained.
4. Security
AI problems with data naturally lead into issues with cybersecurity. Because AI is so dependent on large amounts of data, there is a massive opportunity for bad actors to take advantage of these data sets. They could gain access to private data, purposely corrupt the system, manipulate it to make false decisions and more.
Implementing AI in your organization requires strong data management practices such as access control, encryption, removal of duplicate data and proper documentation. For those who develop AI, transparency, testing and auditing are essential to catch and correct security issues.
5. Infrastructure
It’s tempting to visualize all that data floating around in space or up in “the cloud,” but the truth is that even cloud data takes up physical space, as it needs to be stored on servers. Because artificial intelligence requires a lot of data and processing power, building the infrastructure to support it can be a challenge.
Like some of the other challenges of artificial intelligence, this one will have a greater effect on businesses developing and deploying their own AI. If you use an out-of-the-box AI solution, like a chatbot or certain fraud prevention tools, your data and processing power will likely be the responsibility of the company that produces it.
6. Cost
With data, infrastructure and hiring the right employees, the costs of AI can seem astronomical. It’s true that some applications aren’t cheap, but as cloud computing and processing becomes more powerful and AI becomes more commonplace, the technology is likely to cost less.
Still, cost is not necessarily an artificial intelligence problem. Business owners need to think long-term and consider all the benefits of AI before they forego these technologies due to budget. AI applications can often reveal new efficiencies in your operations, cutting down on manual tasks and freeing up your employees to better serve your customers and come up with your next big idea. Ultimately, AI can save you money.
7. Legacy systems
Integrating with existing systems isn’t just one of the most common challenges of artificial intelligence – it’s a challenge that faces any new technology. Businesses often have complicated technology stacks with multiple pieces of software that have been added through the years. Whether you’re replacing just one piece of the puzzle or the entire thing, the integration process takes time.
Add in the complexities of human behavior – like resistance from your workforce or the need to implement new processes – and the challenges multiply. Great leaders will need to spearhead the implementation of AI with a strong vision and effective communication.
8. Public perception
Why might your workforce be hesitant to embrace artificial intelligence? The public perception of AI is often poor. Some people believe that AI is going to take human jobs and leave them in the dust. Others see the portrayal of powerful, human-like machines in movies and fear an AI takeover. Yet neither of these things are true.
An AI economy can reduce repetitive tasks, increase productivity and allow us to focus on projects that are more meaningful. But humans tend to fear what we don’t understand, so communication is key. One of the biggest challenges of artificial intelligence is educating your workforce and the public on how it will help them, not hurt them.
Artificial intelligence doesn’t have to be intimidating. With the right knowledge and preparation, you can turn these AI problems into opportunities to improve your business strategy and grow in new ways.
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