Artificial intelligence (AI), particularly generative AI, has rapidly taken over the business world, pushing organisations closer to new realms of efficiency. Its ability to streamline processes and automate time consuming activities has made its implementation a top priority across the globe.

However, despite its inherent benefits, there are significant concerns and reservations surrounding its unanimous use. For many, AI represents a route to the unknown, which is causing substantial concerns over job security. In fact, recent research has indicated that 39 percent of the British public fear that AI will lead to job displacement.

Creating a culture shift

It is undeniable that the future success of many organisations will hinge on their ability to utilise AI. If its implementation is feared and nobody is properly trained to work in conjunction with it, AI will be ineffectively used, productivity will be damaged, and any return on investment (ROI) from AI-based activities will be jeopardised.

Business leaders must ensure that there is a company culture where employees want to understand how AI is being implemented and how to better facilitate it. Without this, employees are likely to fear what they don’t understand, causing these tools to hinder productivity rather than streamline it.

Before implementing AI, organisations should look to educate their staff on the exact areas it is going to be used for, how it will impact their roles, and how this can be leveraged to enhance their performance. This will fill in the gaps of what was previously “unknown”, preventing any job security anxieties.

Once employees understand how AI can be used to help their day-to-day performance, they can embody a culture based on better employing these tools. A culture that understands both how AI consumes data and the role this plays in improving productivity, can substantially enhance AI performance and employee productivity simultaneously.

By harnessing the full value of AI, organisations can reap the benefits of utilising larger sources of data, simplifying cryptic information, or even improving the customer experience.

Creating enriched insights from masses of data

A typical large organisation uses an average of 177 software-as-a-service applications. As each process, workflow, and service is used more, the volume of data increases exponentially, which leaves masses of data unused.

By creating a culture that understands and supports the use of AI, organisations can overcome data complexity issues and realise the full value of their  data. AI models can rapidly learn and act to anomalies, trends, and business needs. This utilised data can help produce newly enriched insights, streamline processes, improve business agility and facilitate superior business performance.

For example, AI models in the banking sector can identify and predict spikes in mobile application use whilst ensuring that the right information is displayed to users without service interruption.

Simplifying language interfaces

By understanding what AI’s biggest strengths are, employees can simplify tasks that were previously time consuming or complicated. For example, AI can respond to and generate natural language, hereby, democratising technical tasks. In IT operations management, this can be used to provide clear, easy-to-understand summaries of problems instead of cryptic error codes and, with large language models (LLM) for generative AI, it can even offer a solution.

With increased understanding of what AI is capable of, employees can also appreciate where its limitations lie, such as resolving more complex incidents like integrating data from multiple unstandardised systems. Employees can dedicate more of their time to these areas, as they know AI can expedite the other areas of their job. Consequently, developers can work across systems faster with ease, and create a more complete work service compared to if AI and employees were to work independently.

Enhancing the customer experience

As well as improving performance internally, when AI and employees effectively collaborate, it can also augment performance externally, such as the customer experience.

Indeed, a typical contact agent will process and learn from previous conversations with customers refining their responses and actions to ensure more effective and relevant user engagement. However, when this is incorporated with LLMS and generative AI, brands can offer more relevant and customised engagements that give consumers the ability to do what they want, when they want, leading to a sale and greater loyalty.

Removing the fear and propelling organisations to the future

AI symbolises a future of automation, which in turn represents potential job security implications. However, this is the case when an organisation carelessly implements these tools without considering how its employees will interact with it — in which case they won’t see substantial benefits in any area.

AI should be seen as a tool that can enhance the efficiency and productivity of the workforce. It can be a great resource for simplifying complex tasks, enhancing the degree of insights that can be drawn from masses of data, and improving the range of responses an employee can give to their customers.

When AI is implemented into a company that has a culture of wanting to capitalise on the benefits of AI, whilst improving individual performance, it can be the ultimate ‘silver bullet’ in both improving internal processes and transforming the quality of work employees produce.