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AI, automation, and data proving: A potent mix for early adopters
Wed, 28th Feb 2024

While the capabilities of artificial intelligence-powered tools are growing by the day, increasing numbers of businesses are finding they can deliver practical benefits.

Widely used for years, AI reached an inflection point with the launch of ChatGPT in late 2022. Since then, companies such as OpenAI, Microsoft, and Google have been racing to integrate AI capabilities into a range of existing business applications and services.

Generative AI, which uses large-language models (LLMs) to create new outputs, is also being used by businesses to create anything from marketing copy and emails to computer code and images.

Combining the elements
A successful AI business project requires three key elements. Firstly, the business needs to choose the most appropriate AI tool for its needs. Acting as the ‘brain’ of the project, these tools vary widely in capabilities and sophistication, so careful evaluation of options is important.

Secondly, the project will require ‘automation’ tools, which act as the ‘body’. There is little point in having AI making decisions and suggesting outcomes if those cannot then be undertaken by automated workflows.

Thirdly, a project will require data. This becomes the ‘energy’ that powers the AI and allows the automation layer to deliver maximum value. This data is likely to be stored in several locations across the business, so thorough and secure aggregation is likely to be required.

Start small and grow.
Rather than taking a ‘big bang’ approach to AI deployments, many businesses are finding it advantageous to begin with a modest pilot program and then grow over time. This allows the capabilities of the new tools to be understood and the ways in which they can add value explored.

For example, some businesses begin by introducing Microsoft Copilot to a pilot group of users. They can explore the capabilities of the AI-powered chatbot and report back on the benefits it can deliver. Once these are clearly understood, usage can be expanded across the organisation. 

Designed to be integrated with existing Microsoft tools such as Outlook, Word, Excel, and Teams, Copilot acts as an intelligent digital assistant that can do everything from taking notes during a meeting to summarising documents and creating ‘to-do’ action lists.

Another area gaining increasing attention is the overlaying of generative AI models on top of a business’s own internal data. This data could be anything from customer databases and transaction records to management reports and market analysis documents.

By making use of a generative AI tool, staff can query this large volume of data using natural-language prompts and gain insights that previously would have taken extensive time and effort to produce. 

A third use case is being seen in organisations that need to manage large volumes of incoming emails. These could be anything from enquiries from customers querying orders to requests for returns or refunds.

AI tools can be used to automatically assess each incoming email and determine what the sender requires. The email can then be routed to the most appropriate department within the business for follow-up action.

The tools can also provide regular reports on the volume of emails being received while also conducting sentiment analysis to determine the mood of the senders. If large numbers are determined to be unhappy, additional follow-up actions can be recommended.

Evolution and security
With massive investments being made by multiple players in the AI space, the capabilities of the resulting tools and platforms can only increase. This means their ability to improve business efficiency and lower operational costs will continue to grow.

As adoption rises, it will also be important for business to carefully consider the security implications associated with AI usage. The tools may expose sensitive data to users who are not authorised to view it. Alternatively, they could result in confidential data being made available outside the organisation.

For these reasons, it will be important to conduct regular reviews of the security measures that are in place. The data sets being accessed and used by AI should also be evaluated to ensure misuse is avoided.
 
It should be remembered that AI is far from being a silver bullet, but its ability to add business value will continue to grow. The organisations that manage to harness its considerable potential will be well placed to achieve a significant competitive advantage.