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Dispelling the AI myth: Four use cases for AI in the enterprise

Enterprises can use AI to identify customer pain points...

A new report shows the number of AI companies in the UK has surged 600 percent in the last decade, from 180 in 2011 to more than 1,300 today. As keeping up with markets and competitors remains one of the main challenges for modern companies, AI adoption has become a key goal. In Gartner’s 2021 CIO survey, 69% of boards report accelerating digital business initiatives to improve business operations and speed up their ability to get new, high quality products and services to customers quicker than ever before.

When adopting new technologies to achieve these goals, many are looking to AI for assistance. European businesses’ spending on AI is set to reach $12 billion this year. But for many organisations, AI can be seen as a difficult endeavour or even a pipedream, especially for organisations still wrestling with upgrading legacy IT. Knowing how and where to apply AI within the business can be another huge barrier, especially as many companies simply don’t have data science skills in-house, writes Anita Weppenaar, SoftwareONE Cloud Services Practice Lead for UK, Ireland and South Africa.

What’s more, there’s still a lot of hype around AI, with much of the conversation revolving around robots, super computers and driverless cars. Businesses must think about AI in real-terms, and consider the practical applications. Organisations can benefit from AI on a smaller-scale to improve internal business processes. Adopting AI to improve just one process or workflow can enhance data analysis, optimise business decision-making, and achieve greater outcomes at a quicker pace. To help dispel the myths and understand its use in the enterprise, here are four solid use cases for AI in the enterprise.

Four use cases for AI in the enterprise

  1. A Better Customer Experience – AI can be used to analyse customer activity and trends, see where pain points are, and identify any additional products they may be interested in. For instance, if users are regularly engaging with certain features, or experiencing performance issues on certain pages, AI can immediately identify these issues and provide the business with suggestions to auto-resolve them. Similarly, user patterns can predict future opportunities to drive growth by providing businesses with recommendations on new services they may like to see.
  2. Improve Business Efficiency – AI can also be used to remove toil work from business processes. Over 40% of workers spend at least a quarter of their week on manual, repetitive tasks, with email, data collection, and data entry occupying the most time. AI tools can perform those operations in real-time, as well as learn from previous patterns to suggest optimisation for business processes. This can result in huge time savings for employees, who are then able to focus their efforts on tasks that drive additional value for the business, such as app development or customer service.
  3. Increase Data Security – AI can monitor user activity and learn to detect potential security threats, both internally and externally. For instance, an AI-based security solution could regularly analyse when certain employees log into a cloud solution, which device they used, and from which location they accessed the cloud data. If one night, a user logs into their account at 3am from another country, the AI would notice this activity was unusual and can alert the organisation’s security team.
  4. Identify New Business Opportunities – AI can analyse market, customer, and company data to find patterns that can lead to new opportunities. This could include using AI to automatically assess the validity of form-fills to identify quality leads. An official company email will be automatically sorted as a high-quality lead, while a “” email address will be sorted as low quality, meaning organisations spend less time cleaning datasets, and more time capitalising on hot leads.

The most important thing when it comes to adopting AI is identifying a clear roadmap for which processes could most benefit from its implementation, what value it can bring, and how this can realistically be achieved. Whether AI strategies are devised and carried out by an in-house team or a technology partner, it’s crucial to understand your organisation’s needs and its use case for AI. This can help inform the decision to either custom-build AI for a specific process, or to adopt a tool from one of the major tech vendors – think Azure or AWS – that has AI built-in, so you can transfer the benefits over to your own business.

See also: The UK gov’t has a legacy of failed IT projects: These 6 things need to change, says NAO