AI isn’t a new trend. However, over the past few years, it has become more intricate and its uses more sophisticated.

Using AI, companies will be able to make strides toward creating ever more intelligent products and services.  It’s set to become a very real presence in organisations across every sector.  Its influence has caused some thinkers to believe that AI could augment nearly every job in every business process. As such, workers should anticipate working alongside machines in the 2023 workplace.

If you have plans to introduce AI into your organisation and leverage the advantages of this technology, there are some things to consider first.

What should I consider before I introduce AI?

First and foremost, you must consider and identify the problem you need the technology to solve.  For example, issues such as low productivity or efficiency can impel the need to improve processes through automation and the reduction of duplicated actions.  It’s true that AI has a lot to offer in solving these types of problems but introducing them requires careful consideration. It’s important to make sure that you maintain a human-centred and ethical approach.

5 things to think about before introducing AI.

Understand the technology.

AI is a single widely used term, but within it there are a range of technologies. Machine learning (ML) describes technologies that analyse existing data to discover new insights so if you’re looking to establish seasonal trends or patterns to inform your next move this may be useful.

ChatGPT is an AI tool receiving huge amounts of media attention. It falls into the category of generative AI (GAI). GAI takes the cumulative learning from large general collections. It then creates a result based on general trends and likelihoods found in this data. This facet of AI can used to generate insights from existing organisational documents, for example.

Be clear about the problem.

The difference between ML and GAI can be used to demonstrate how the choice of AI must be shaped by an identified need.  ML can be used for retrospective learning, whereas GAI can be used as a way of extrapolating forward and generating new materials.

Some tasks, such as process automation may require both. Many tools support tasks such as automation and can chain together multiple steps in the creation of a solution.  For example, IfThisThenThat (IFTTT) and Zapier can connect steps together in a non-technical way.

Know the data protection implications.

Using AI tools may involve data transfers that have significant implications across your business. Your policies and training procedures will need to recognise this concern. Impact assessments may be required, and you’ll need to consider your ability and procedures for handling subject access and deletion requests.

Data protection provides legal safeguards for your customers and employees. Any move towards AI implementation needs your data protection team to be involved from the very beginning. And if you don’t have a team in place, you’ll need to look at the possibilities amongst your current workforce.

Learn your legal responsibilities.

Legal responsibilities go beyond data protection concerns.  For example, one consideration with AI is the possibility of bias.  For example, if you wished to automate your applicant screening processes, could you guarantee that everyone would be treated equally regardless of any protected characteristics they may possess?

Businesses should be sure that they understand enough about the proposed system to inform their equality assessments, and not just rely on the marketing or sales information provided by the software provider.

Data is an important asset for your business, so another legal consideration is data ownership.  For example, GAI relating to images has already attracted significant criticism from existing artists over in the US who claim their images have been used to train these new tools.  In addition, many consultancies and law firms have restricted the use of GAI for fear of breaching ownership regulations and compromising client data.

Keep the human touch.

Introducing new technology is rarely a total solution. Introducing AI is not in itself a replacement for people or processes; technology works best in organisations that align its people, the processes, and the technology. These technologies are tools that humans use, rather than substitutes for human involvement and engagement.

It’s evident that we can expect so much more from AI in the coming years. The potential it has for organisations and their customers are far-reaching.  Despite this though, it’s not an addition that should be unconsidered.  Its deployment raises many ethical and practical issues regarding organisational data and the structural processes within the business.

Can we help?

Do you need the technology talent to advise and deliver on your organisation’s AI ambitions? Let Ignite Digital help. Reach out today to see how we can help find the people to bring AI to your organisation.

About the author: As a founder of Ignite Digital Talent, I lead our brilliant team to ensure we deliver time and time again for our clients. I also stay closely networked with industry influencers to ensure we are well placed to understand the issues and challenges our clients face.

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