Using Artificial Intelligence (AI) in your business – Challenges and Opportunities

Using Artificial Intelligence (AI) in your business – Challenges and Opportunities

While ChatGPT and similar AI software programs are in the headlines, over half of businesses already use AI for email & website cybersecurity and banking to minimise fraud. 

This Forbes article found that up to 97% of business owners looked to AI as helping their business in some way, while 40% were also concerned about becoming overdependent.

Top 10 key benefits

AI is playing an increasing role in enhancing customer experiences across several touchpoints. This not only benefits the customer; it also is expected to bring increased productivity and reduce expenses. According to the Forbes Advisor survey, the main areas being:

Chatbots 73% - most businesses currently use or plan to use Chatbots soon to help manage prospective and existing customers' simple requests or questions.

Email optimisation 61% - not only assisting in sorting and prioritising emails, but AI writing tools can also draft emails and personalise them to increase engagement. 

Customer Service 56% - the main areas are understanding the client and improving decision-making, as well as decreasing response times and reducing mistakes. Other areas include personalised services through customer product recommendations and ads, text messaging and phone communication. 

Cyber security/ Fraud Management 51% - AI fraud management systems can identify and prevent various types of fraud, such as payment fraud, identity theft or phishing attacks. They can also adapt and learn from new fraud patterns and trends, improving their detection over time.

Digital Personal Assistants 47% - Voice-powered virtual assistants or virtual assistant voice services like Alexa from Amazon or Apple's Siri utilise Natural Language voice commands and speech recognition technology to interpret and respond to verbal prompts and voice interaction. Google is also working on a new AI personal assistant to perform more personalised tasks,

Inventory Management 40% - by analysing various data sources, such as sales records, customer behaviour, weather, seasonality, promotions and such, AI programs can generate accurate and timely forecasts that can help businesses plan their inventory levels and re-ordering strategies. This reduces inventory wastage and helps maximise financial resources.

Content Production 35% - AI can help to optimise content for search engines and social media platforms, making it more visible and shareable. It can also analyse user data and generate personalised content that resonates with specific customer groups.

Product Recommendations 33% - AI recommendation systems are widely used in e-commerce to suggest products to users based on their browsing and purchase history, preferences, and behaviour. The recommendation system analyses customer data to identify patterns and trends in their purchase behaviour and recommends products that interest them.

Supply Chain Operations 30% - AI is already proving very beneficial across all supply chain stages by optimising inventory management, enhancing warehousing and storage and supporting process automation — helping raise efficiency and productivity, preventing human error, and assisting in limiting supply chain disruption. 

Recruitment and talent sourcing 26% - AI software is already in use for recruitment and can assist in sourcing and screening candidates, analysing resumes and job applications, conducting pre-employment assessments, and even predicting candidate success and cultural fit.

Key Concerns

The main concerns from the survey are:

  • Dependence on technology – shortage of trained employees to implement, monitor and update technology. Additional training requires time and resources. Reputational damage and potential financial impact if AI-generated information is inaccurate or wrong. Vulnerability of systems to breaches of privacy and loss of commercially sensitive data from cyber-attacks. 
  • Job Displacement: As is the case with automation of processes, there's a concern about work and job losses. Tasks historically performed by administrative staff, HR recruiters, software developers, copywriters, etc. are likely to become redundant.
  • Ethical Considerations include the management of bias and fairness.  AI systems, as sophisticated as they are, can still carry biases as guides and parameters have to be programmed in initially. Laws such as the Disability Discrimination Act 1992, Racial Discrimination Act 1975 and the Age Discrimination Act 2004 all apply to the AI process, in particular to HR teams. Therefore, the presence of a trained person to monitor both input and output is essential. 

While AI-powered claims processing systems promise a future of increased efficiency and accuracy, they also bring challenges and ethical dilemmas. As with any technology, the key lies in balancing the benefits with the potential drawbacks and ensuring that the human element remains central to decision-making.

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