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How Artificial Intelligence and Machine Learning could impact your workplace

The rise of Artificial Intelligence (AI) and Machine Learning (ML) are hot topics in the news right now, often accompanied with reports about crime and doomsday predictions for the future. Recent innovations in AI are certainly changing the landscape for many industries at an incredible pace. Have you considered what this might mean for your business and people?

Artificial Intelligence, AI, Machine Learning, ML
Artificial Intelligence, AI, Machine Learning, ML

In this article I am going to focus on practical implications for today’s workplace from AI and ML, with an eye to future considerations, whilst avoiding any scary predictions which have been covered elsewhere. I will also focus on the people and HR related points, specifically:



Why you should consider the impact of Artificial Intelligence (AI) and Machine Learning (ML)


Technological advances have always impacted people. Imagine how many fewer people were needed to move things around following the invention of the wheel. In the 18th century around 80% of people worked in agriculture, now in the UK that figure is nearer 1%, yet we all eat much more plentifully than the average person back then. Much like these advances, developments in Artificial Intelligence (AI) and Machine Learning (ML) will drive significant changes in what people do and what organisations are capable of doing in the future.


Making Artificial Intelligence (AI) and Machine Learning (ML) technologies part of your established business process


The rate of AI and ML development is impressive and can present benefits to traditional techniques. In the HR sector for example, advances in recruitment, onboarding and data management will undoubtedly remove labour intensive elements of certain job roles.


From a people perspective it is much better to engage staff in incorporating AI and ML as part of an established business process. In this way the AI and ML tools can be trialled and tested to ensure that they consistently deliver desired outcomes.


The capacity plan for people can be adjusted to reflect a change in role from 'doing', to an emphasis on training and testing the AI and ML tools and validating the output. There is much commentary for the potential for bias from AI and ML and so if there is an established business process it is far more likely that can be spotted in testing, managed through observing actual results and iterated in the models.


In a nutshell. embracing AI and ML tools may result in the ‘active’ part of the role being less people intensive. However, accumulated knowledge and skills can be valuable in training and validating outputs.


Risks of informal use of Artificial Intelligence (AI) and Machine Learning (ML) technologies by employees


The informal use of AI and ML technology by employees can expose organisations to a full range of risks, particularly in data protection and the reputational risk of getting things badly wrong for customers and operations. For some businesses, prohibiting informal use of AI and ML technologies may be the right decision but enforcing this may be problematic.


It therefore seems sensible to have some guidelines for employees in place to regulate and also monitor use. For example, many praise the benefits of ChatGPT, however unchecked, it is not yet ready to be used in an uncontrolled environment. Furthermore, certain data may need to be fed into the AI and ML tools to either train them, or to generate the required output from a third-party algorithm. Insufficient due diligence around the permission to use such data and understanding of how it will be used and stored by the third party underlies the data protection and reputational risk. There is also the consideration of how the output will be used both by your organisation and the third-party provider.


It remains important to ensure that employees and businesses leverage AI and ML efficiencies without unwittingly exposing the organisation and themselves to unnecessary risks of using informal and untested tools.


Recommendations

  • Embrace the technology and see what it can do to enable better things for your customers.

  • Identify areas where technology will have the biggest impact on efficiencies and cost reduction

  • For customer facing and other key areas we would recommend only using AI and ML as part of a tried, tested and established business process.

  • Encourage experimentation and informal use of AI and ML as applicable to your organisation in a lower-risk environment. Once tested and established, then move key learnings to be part of established business processes.

  • Incorporate the potential of AI and ML in your related policies. Be clear which technologies are acceptable and when they can be used.

  • Promote innovation using AI and ML through training.

  • Actively consider how AI and ML enabled change will impact the roles in your organisation design and structure.

  • Analyse the effects of AI and ML on capacity planning. Think about which roles and tasks are now “redundant”, what new/different work is needed, and the training and support required to optimise that.


How Hummingbird HR Services can help


If you recognise these issues and are facing some of the challenges raised in this article, we would love to hear from you. Please contact annette@hbhrs.co.uk to discuss any concerns or issues within your business.





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