Over the past couple of years, artificial intelligence has made its mark on the world of work and it has become evident that it is here to stay.
While AI has come with unique challenges, for example raising questions around ethics, many have incorporated AI into the inner workings of their day-to-day. We have seen the adoption of such tools fuelling productivity and streamlining workflows, as well as aiding in the simplification of tasks such as data modelling, forecasting, and reporting.
Whilst GenAI, Machine Learning (ML) and Deep Learning (DL) AI tools do pose unique challenges when considering how they can be implemented within business processes, they should ultimately be viewed as just another business change. Therefore, organisations should approach it in the same way they would any other business change.
With this mindset, businesses can confidently adapt their processes so employees can cement the use of AI into areas of work where it can have maximum impact.
AI is transforming businesses
From processing large amounts of data with ML algorithms to DL fraud detection, the plethora of AI use cases has meant that its progression over the past year has left no industry untouched. Thus, it has paved the way for some transformative changes in how businesses tackle problems and develop solutions.
While there are too many to list, just a few examples include cyber security and risk management, customer support, code generation, and the automation of tasks.
These are transforming businesses for the better. AI’s time-saving qualities mean teams can focus more resource on creative processes, for example using data analysed by AI to inform strategy. It is also offering a higher level of accuracy and consistency by minimising opportunities for human error. These benefits are ultimately leading to more efficient processes and increased workplace productivity.
Determining where AI can aid productivity
While one of the major advantages of incorporating AI into workflows is increased productivity, for businesses to see maximum impact, it is critical to do internal research to identify bottlenecks and pain points where AI could help.
Businesses can incorporate multiple tactics to achieve this. For example, pulling together a report on the tasks that are taking the most time or surveying employees to understand what challenges they face in day-to-day work and where they see AI could have the biggest benefit.
This could include the tasks that they feel could be simplified. Many employees are already using AI so taking time to learn about their experience with it can also lead to shared learnings for the wider business.
The dangers of ineffective AI strategies
If an organisation is serious about incorporating AI, a dedicated strategy is the best way forward. Creating a loose AI strategy, throwing it at a wall and hoping it sticks is unfortunately a tried and tested method of what not to do.
Therefore, to reap the rewards, it is necessary to invest time in developing an effective strategy. To do so, businesses must first set out clear objectives and appoint a leader and/or team accountable for driving the strategy and rollout within the organisation. In fact, new research from Grayce revealed 39% of FTSE 350 businesses already have a dedicated head of AI.
To set objectives it is worth considering why your business wants to use AI and what a successful implementation of AI would look like to you. For many, this does mean maximised productivity. Therefore, learnings identified from current business processes should be used to inform the objectives and strategy.
Once the objectives have been set and a strategy has been put in place, training employees is an essential step to roll out. Clear communication with employees about the tools to use, how to use them, and the benefits of doing so will ensure each employee feels confident in using them and is using them effectively.
For example, Grayce recently launched an AI Lab to upskill its analysts covering a variety of fundamentals from how to write effective prompts to ethical implications.
Approaching ethical issues in AI
One of the largest uphill battles businesses face when attempting to implement an AI strategy is ethics, with 41% of C-Suite professionals stating that they are worried about this, according to the research by Grayce. Scepticism surrounding AI is completely understandable, not only from a moral and bias perspective, but a privacy and data protection standpoint too.
This is why AI governance is so important. AI governance ensures safety and risk mitigation, which provides a layer of trust when deploying the use of AI tools in businesses. Established frameworks and rules within a business’s strategy will ensure employees feel confident when utilising these applications. On top of this, clients of the company will also have the assurance that their data safety and privacy is at the forefront of an organisation’s priorities.
The businesses stance on such questions must be included within all training rolled out to employees to ensure they know what is expected and that they are upholding standards.
The importance of change management
Effective change management ensures a smooth crossover period that is minimally disruptive and should empower employees into feeling involved and satisfied with the changes. For any organisation implementing change, change management is an essential cog in the transition process. Incorporating new technological advancements, such as AI, into business workflows and processes takes a certain level of management that without, can cause transformation projects to fail.
As with any change and transformation project, it is all about good planning and clear communication with those impacted. This is why AI should be seen as just another business change and should be treated as such.