Learn how to drive value from AI with The Data Lab – Q&A with Anna Ashton Scott

Artificial intelligence, more commonly referred to as AI, is already reshaping processes across industries like banking and finance, and marketing, and is set to become increasingly embedded in workflows across the board in the coming years.

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To support businesses in navigating what AI could do for them, The Data Lab have developed an online course on driving value from AI. Matthew Paton, BE-ST Impact Manager, sat down with Anna Ashton Scott, Programme Manager at The Data Lab, to delve into the role of AI in society, ethical considerations, and the essential AI skills for business leaders and insights from the course.


Matthew Paton: Starting with a simple question, what is AI?


Anna Ashton Scott: Not so simple, but a good place to start! AI is the integration of human-like processes or intelligence into machines. In a business setting, we understand AI as something that gives us the ability to respond rapidly to opportunities based on trusted information, change processes without human intervention, and gain a competitive advantage.


But there is no one-size-fits-all definition. The key message from the Driving Value from AI course is that participants need to formulate their own understanding of AI's value for their specific business context.


Matthew: What role is AI playing in society at the moment?


Anna: AI is already making a noticeable impact across various sectors, from automating time-consuming tasks to aiding medical diagnoses. Its applications extend to personalisation through digital assistants like Siri or Alexa, security with automated scans for malware, and even large language models like ChatGPT. AI will have particularly huge societal implications, especially in terms of skills and work.


Matthew: On that, will everyone have to use AI in the future or will it be left to specialists?


Anna: AI literacy is becoming essential for professionals across various roles, not just limited to those in technical positions. I read a good article recently that said something along the lines of ‘You will not be replaced by AI, but you might be replaced by someone who understands how to engage with AI.’


While specialists like machine learning engineers and data scientists will always be needed, a general understanding of AI will be increasingly valuable for workers in different roles. It'll become challenging, if not impossible, to avoid interacting with AI at some point in your work or personal life.


Matthew: Are companies bringing onboard new talent for AI work or integrating it into existing workflows?


Anna: The current focus is on automating existing systems and rethinking workflows to align with AI capabilities, while increasingly upskilling existing employees.


Recognising the skills gap, organisations like Unilever are redefining jobs as collections of skills and tasks, fostering a dynamic internal marketplace. IBM also recently said it anticipates that 40% of its workforce will need to be reskilled due to AI.


Unlike companies the size of IBM, SMEs and startups may not have the resources to upskill existing staff but could benefit from an injection of AI talent to work on short term projects through placements like the one The Data Lab runs with master's students at Scotland’s universities.


Matthew: How are businesses harnessing the potential of AI to drive value in their processes?


Anna: Companies can leverage AI for learned decision-making, process optimisation, and gaining a competitive advantage. Examples include the automation of tasks like cropping thermal images in homes – which is the focus of Dundee-based company IRT. Automation has been reported as enhancing job satisfaction in finance and manufacturing as it frees people up to work on more interesting projects.


AI is seen as a tool to streamline operational tasks and create efficiencies.


Matthew: What are some of the ethical considerations when talking about, promoting, or deploying AI solutions?


Anna:  Data powers AI, and AI makes decisions at pace without human intervention. So, if you're feeding your AI solutions with bad data, you will get poor results and potentially create outcomes you're not proud of.


Eliminating bias and unrepresentative datasets is crucial to ensuring ethical AI decision-making. Organisations must be vigilant in removing bias from data, and if you want to make truly effective decisions, you need to build diverse teams representative of our society.


Matthew: How does The Data Lab’s course help business leaders sound credible when talking about AI?


Anna: ‘Driving Value from AI’ is a self-directed online course designed for leaders and team members responsible for AI within their organisations. It provides practical insights, diverse perspectives, and a personalised action plan, making it accessible to individuals with varying levels of AI knowledge.


The course focuses on developing leadership skills, providing participants with a credible voice, an inspirational vision, and a believable path to success when discussing AI. It emphasises human skills such as curiosity, pragmatism, and empathy, guiding leaders to confidently communicate about AI techniques and opportunities.


Matthew: Should companies be preparing ‘AI strategies’?


Anna: In short, yes. This will vary depending on your company’s level of data and AI adoption, but business leaders should be proactive in preparing AI strategies that are aligned with their business’s strategy. This will ensure that you are ready to implement new software and processes ethically and effectively.


Our course encourages leaders to create an AI vision, understand the uses and limitations of AI, and take steps to develop an AI plan to achieve their goals. Crucially, strategies should also be flexible to allow organisations to adapt to the rapidly changing AI landscape.

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If you want to navigate the AI landscape with confidence and credibility, equip yourself with the skills needed to understand, implement, and communicate about AI in your organisation.