By Kit Cox
Artificial Intelligence is a hot topic right now, and for good reason. When implemented correctly, AI has the potential to revolutionise businesses of any size. Imagine your team spending less time on repetitive tasks and more on strategic, value-added work. That’s the promise of AI. But let’s be honest – the journey to AI innovation isn’t always straightforward.
Understanding the AI maze
Diving into AI is a complex endeavour. The technology is changing week by week, bringing new challenges and opportunities with it. Additionally, there’s the human element to consider. Employees might be wary of AI, concerned about job security, or simply uncertain about how it will impact their roles. Then there are the technical challenges like security, compliance, implementation costs, and the need for training. If your IT systems are outdated, that’s yet another hurdle to clear before you can fully embrace AI.
Planning is key to the success of AI
These challenges highlight the importance of thoroughly understanding your current business processes, identifying potential use cases, and setting clear goals for what you want to achieve with AI. This preparation helps build a strong case for AI and allows you to anticipate and address potential roadblocks.
Having a business orchestration tool can provide a clear overview of your operations and pinpoint where AI can make the biggest impact. It’s like having a strategic roadmap for your AI initiatives.
Mapping out an AI strategy
The best way to determine which AI tools will benefit you most is to conduct a comprehensive review of your business processes, particularly the manual and repetitive tasks. For instance, if your workflow involves extensive form management, AI tools such as Intelligent Document Processing can automate data entry and save considerable time. Similarly, if you’re overwhelmed with service emails, tools for email triage and sentiment analysis can greatly enhance efficiency.
AI doesn’t represent all forms of automation
AI is a broad term, so it’s important to differentiate between its various types. There are AI models developed by data scientists to predict outcomes, narrow-field AI for specific tasks like invoice processing, and generative models like ChatGPT that have a wide range of applications. Understanding these distinctions helps you see where AI can be most effectively integrated into your processes.
Implementing automation technology such as RPA, Rule Engines, iPaaS, or low-code solutions requires a different strategy compared to implementing AI. Knowing how to make these distinctions means you’ll have a better understanding of the unique applications of AI, making it easier to understand where they can fit within your processes.
Embracing GenAI safely
Security concerns around AI are valid, but they shouldn’t deter you from leveraging AI’s benefits. A recent survey by Cisco found that one in four companies had limited the use of generative AI tools at work due to concerns around security. It can be daunting to proceed with AI, but the truth is there are many scenarios where the technology can be deployed with minimal risk. The answer isn’t to put a blanket ban on the use of AI but to carefully assess and manage where the risks are.
For creative professions such as graphic design, coding, or copywriting, embracing GenAI is a low-risk endeavour. In our own organisation, our Copywriters rely on AI for proofreading, while our Coders use it to write their first draft of code. These teams, which have established procedures for testing, quality control, and validation, find AI invaluable for accelerating routine tasks.
Approaching GenAI in these steps is a good place to start: Identify all employees whose roles involve creative tasks, form task forces to find the best AI tools for their needs and procure low-risk AI tools to assist across the organisation. This method boosts productivity and creativity while managing risks.
Empowering employees with AI
To make AI a priority, empower your employees to lead these projects. Moving beyond the IT department, allow business users to access and apply AI models directly to their work areas. This approach fosters a deeper understanding and ownership of the technology.
For roles associated with ‘delivery,’ ‘process,’ or ‘execution,’ it’s crucial to establish safeguards around GenAI and manage risks. It’s necessary to have a method for measuring expected outcomes and a clear policy regarding data management and the use of organisational data in training other models.
Unlocking AI potential
When used effectively, AI can save time, reduce manual tasks, and allow customer service teams to focus on more valuable work. By targeting inefficient processes, AI can make a significant impact, rather than taking an unfocused approach. Businesses should empower their employees to take the lead on these projects. The key is to move beyond seeing AI as simply a task for the IT department. When off-the-shelf AI models are made accessible to business users, they can directly apply these tools to their work areas, enabling a deeper understanding and ownership of the technology.
About the Author
Kit Cox is the Founder and CTO of Enate. Kit has been passionate about technology since childhood, starting coding at the age of 10. He built Enate’s workflow orchestration and AI platform to help businesses automate manual tasks and deliver on time. Global companies like TMF and EY use Enate to streamline their operations.
