Generative AI is very useful
As we move past the initial excitement around AI, the technology is now being applied to a wide range of real-world applications.
Generative AI is currently most used as an assistant or “Copilot”, helping improve efficiency and effectiveness at work by automating many of the repetitive aspects of a task. This frees individuals to concentrate on areas where they add most value.
For example, in education, generative AI can read student test answers, mark them and provide helpful notes for improvement, freeing up teachers to teach. In addition, the AI can provide detailed insights into student performance and suggest areas where additional assistance may be required.
The opportunities are endless…
…when used in the right way!
Generative AI has been trained to give responses to natural language questions. These can be quite sophisticated – for example, analysing a customer email to determine the mood and tone of the writer. It can also create content – from images to code.
But the heart of generative AI is probability and its answers will vary slightly, even for the same question. Sometimes, it will even “hallucinate” (invent answers). This means the technology has to be used with care to ensure the benefits without the risk of undesirable outcomes.
A little planning goes a long way, ensuring that the AI solutions are designed from the ground up to be robust, reliable and add consistent value to the organisation. See how generative AI can help you!
What is Generative AI
Generative AI is a relatively new technology that allows computers to mimic human responses to questions.
It does what traditional computers find hard – handling with imprecise or poorly defined questions and creating answers that often look similar to those a skilled human would create.
Unlike traditional predictive AI, generative AI can be used immediately, without additional training, making it much faster and lower cost to deploy.
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Generative AI in customer care
One of the first uses of generative AI has been in customer care. The traditional “press 1 for sales, 2 for support,…” call centre can be replaced with an AI that is able to respond to customer questions in natural language, either via voice or using a chat interface. For example “How can I help you today”… “I want to open a US dollar bank account”.
Swedish fintech Klarna has used AI extensively and now some 75% of all support calls are handled completely by AI. Moreover, the company claims that customer satisfaction levels for the AI support is as high or higher than with a human (in part because the AI response time is much faster). This frees the care team to handle the most challenging customer issues more effectively.
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Generative AI in analysis
Many roles in banking relate to searching for data, analysing it and synthesising it into reports which are the basis for decision-making. The data is often scattered across multiple sources, in different formats and with little consistency in the way it is written. Generative AI is able to connect with conventional software to capture this information, analyse the documents, extract the important information and both store it for later processing (for example in a database) and directly create reports that summarise the results.
For example AI solutions continuously scan for company reports as they are published, extract the relevant information and create prioritised lists of information for analysts to massively reduce the work needed to search the market for investment opportunities.
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Generative AI in risk management
Traditionally risk management occurs at fixed intervals (for example an annual risk audit). Generative AI can be used to continuously monitor a risk profile and highlight anomalies as soon as they are identified. This information is presented to risk managers as a prioritised list of action items, allowing expert teams to focus their energies on the most pressing issues.
We remain at the dawn of the new AI age. The technology is showing great promise and continues to evolve rapid pace. It is likely that generative AI will be as disruptive as the Internet in terms of its impact and reach. Like the Internet, it will open up new ways of working and new business models that will provide customers with effective, more responsive services.
In that context, banks need to evaluate their AI strategy to ensure it balances growth potential with cost and the internal changes needed to adopt it effectively.
The banking sector is forecast to be one of the most active AI adopters. AI can analyse vast quantities of data and is resilient to unstructured information, making it well suited to environments where data is scattered across multiple legacy systems.
With such a wide array of possible applications, the key is selecting those that are most beneficial and building not just the technology but also the organisational structure to fully embrace the opportunities of AI.
Delivering Digital Transformation with Responsible AI
It is easy to get started with a simple clear approach:
- AI audit – What AI does the bank use today and how are they managed
- AI Governance – Put in place a simple but effective AI governance process
- AI Opportunity Discovery – Map the places where AI can have most impact
Getting started with AI is about choosing the right problem. One with clear business benefit, that can be readily integrated into your existing systems. And one that aligns with the ethos and brand to enhance the customer experience.
Talk to us to start your AI Transformation Journey!