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What is artificial intelligence?

Artificial intelligence (AI) involves using computers that can simulate human intelligence. AI software uses fast, repetitive processing and algorithms to "learn" from large amounts of data and complete decision-based tasks. Find out more about the opportunities offered by AI, as well as its limitations.

AI and cognitive computing

This eLearning module outlines what cognitive computing technologies are most relevant to finance, alongside explaining common misconceptions about the technology and AI. It also covers the benefits, how to get started and includes case studies.

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Artificial intelligence (AI) is not a new technology. For decades, futurists have been predicting a world where human-like computers take over many of the tasks of daily life. This vision remains to be realised but recent advances in machine learning, and in particular “deep learning”, are now bringing AI out of the realms of science fiction and into the boardroom.

Definitions of AI vary, but broadly speaking it involves machines or computers that can simulate human intelligence. In practice, AI is software that – using super-fast, repetitive processing and intelligent algorithms – can learn from large amounts of data, so that it can adapt and carry out decision-based tasks usually associated with human beings.

Often described as a “disruptive” technology, almost all business sectors are now looking at how AI-based solutions can add value. An MIT-Boston Consulting Group survey of more than 3,000 executives found that four in five believe AI leads to competitive advantage and a similar proportion believes it will increase their company's productivity.

Which human skills can AI replicate?

  1. Learn: Use historical data to develop experience and make decisions.
    For example, choosing the correct response to a question asked based on previous responses.
  2. Understand: Apply context and interpret images and speech.
    For example, recognising objects in images and being able to infer the context of the image.
  3. Interact: Talk and interact in a natural way.
    For example, recognising the intent of a comment to interpret what a user wants to know.
  4. Perceive: Use hearing/sight to gather information from surroundings.
    For example, recognise sentiment, such as anger, in audio files of conversations.
  5. Reason: Grasp underlying concepts, form hypotheses and infer ideas.
    For example, recognising patters in large amounts of ungrouped data.

Business benefits of AI

The most interesting developments in AI centre on machine learning, with one if its subsets, deep learning, becoming the latest AI buzzword. Both of these have been enabled and supported by the exponential growth in data and concurrent increases in computing power.

Advantages of machine learning include the ability to:

  • Process large amounts of structured and unstructured data, providing outputs that can be extremely accurate, replacing and, in some cases, superseding human efforts.
  • Pick up weaker or more complex patterns in data – the software can also be highly adaptive and learn from errors or new cases.
  • Make consistent decisions – tiredness and boredom are not an issue and the technology works without the cognitive biases present in humans (although, of course, the data fed in may contain existing societal bias).

With numbers and other data the life-blood of finance functions, the business potential of AI is clear in terms of improving speed, accuracy and capacity.

The limitations of AI

One of the main limitations is that the technology is only as good as the data it receives: data quality and quantity are therefore critical. Machine learning models can also lack flexibility: they learn to carry out specific tasks.

Any discussion of AI usually returns to the fear that it may drive human beings out of the workplace. But while AI could potentially automate many key finance tasks, it does not yet have the capacity to put the data in context or anticipate an organisation’s specific demands.

Machine learning still cannot reproduce the kind of multi-faceted analysis carried out by the human brain.

Moving forward with AI

The accountancy profession has a long history of embracing technology and, where AI aids greater human insight, it can lead to better decisions and more informed advice.

Appropriate implementation of solutions, alongside skill building in AI and data management, could give accountancy firms and practitioners a competitive edge and offer clients added value.

Almost 80% of the respondents to the MIT-Boston Consulting Group survey expected AI to augment current employees’ skills, with less than half (47%) expecting workforces to be reduced within the next five years. 

Find out more

Learn more about artificial intelligence and cognitive computing by completing ICAEW and Deloitte's eLearning module. This resource includes more details on these cognitive technologies and their implementation, including examples of how they are being used by finance teams and businesses.