AI Magazine speaks with the President & CEO and Jitterbit, Bill Conner, about the growing AI hype and how it can be integrated into a business successfully
AI interest is continuing to boom across multiple industries, yet businesses are still facing the challenges of adoption.
According to the President and CEO of Jitterbit, Bill Conner, an enterprise has on average nearly 1,000 applications and only 28% of them are integrated.
With this in mind, in this interview with AI Magazine, Bill Conner examines how companies can empower employees to leverage AI for productivity gains without the need for job losses. He suggests that organisations will benefit from investing in the correct AI tools for them, which will work to free employees from complex tasks and enable them to focus on more innovative work.
What are the practical challenges businesses face in integrating AI systems with their existing infrastructure and processes?
These challenges can be categorised into three distinct areas: data quality, technical barriers and operational processes.
First, the common challenges for integrating AI systems start with the data. This includes data quality, availability, privacy and security. Not only must organisations confirm data is ‘clean’ and complete, but they must ensure integrity when combining data from multiple sources and formatting it for AI analysis. This is a major undertaking.
Next, organisations will manage technical barriers related to legacy system compatibility, scalability and integration with existing systems — all while continuously monitoring and updating AI models to ensure accuracy and relevance.
After overcoming technical barriers, businesses face human, operational and organisational challenges. This is a broad category and could differ wildly from one organisation to the next, but think of it in terms of comprehensive change management.
How can companies effectively upskill and reskill their non-technical workforce to leverage AI?
It varies by organisation as the amount of upskilling and reskilling is very dependent on the existing in-house technical proficiency. For teams proficient in coding, the issue may be less about acquiring new skills and more about increasing productivity.
As these teams achieve higher coding productivity, their expectation of what can be delivered also increases, so they may need to renew their AI-assisted, low-code options.
For other organisations, the issue is more fundamental. What is needed here is a way to translate business needs — which they can articulate well in their own words — into the code and data integrations they would normally rely on IT to build for them. This requires both business professionals and IT experts to learn how to take ‘novice’ instructions, use AI to code 60% to 70% of the final digital product, and hand it over for quality assurance later in the application design process.
The best AI-assisted, low-code platforms allow everyone from novices to experts to gain productivity by working to the limits of their capabilities.
“AI is not here to replace people; it’s here to empower people,” Bill says.
What strategies can organisations adopt to retrain and redeploy employees, rather than simply replacing them with AI?
AI is about empowering evolution, not a revolution. As such, every organisation should deploy AI at its own pace. There are many factors that determine the speed of this process, including existing employee skill sets and the ability of individuals to work with AI, plus the rate of change the business must achieve.
AI is not here to replace people; it’s here to empower people. It will lower the entry barrier for tasks that once required specialists, such as creating applications, building chatbots in context of business data and automating processes and tasks. When implemented currently, AI enables employees and individuals to take control of their needs and requirements, reducing their dependence on technical experts.
With AI, employees can instruct computers in natural language more easily than ever before, making them more effective and capable. This shift allows individuals to accomplish tasks they previously had to wait for overburdened IT teams or other specialists to handle.
What tangible productivity gains can businesses realistically expect from implementing AI solutions?
AI has empowered computers to converse with humans in natural language, resulting in a substantial increase in employee productivity and operational efficiencies. With the ability to understand human language, AI empowers citizens to fulfil their requirements without relying on experts, achieving independence. Technical experts are only needed for advanced portions or when really necessary.
We are seeing breakthroughs in use cases like research, where AI has already replaced a lot of search engine usage. Some other promising work is in the sphere of bid proposal preparation, where standardised content needs to be collated and reformatted to tight deadlines, and we can see standout successes here already.
AI also facilitates rapid prototyping and idea validation, leading to significant efficiency and operational gains. This is just the beginning; as these technologies mature, more tasks and processes will become feasible. AI will drive the discovery of tasks and processes, integration needs, application, and automation of tasks that were previously beyond reach of citizens.
Instead of replacing humans, AI can be a powerful teammate. Automating tasks frees up employees to focus on areas where human skills can shine more, helping load-balance human productivity to focus on more intelligent and strategic thoughts.
How will the AI-powered businesses of the next few years differ from those today?
AI is empowering a business evolution, not revolution. This is important as organisations look to adopt AI as a choice and at their own pace.
AI-powered businesses of the future — which aren’t that far away — hold the promise of not only enhancing efficiency and productivity, but also democratising access to technical capabilities and addressing a wider range of requirements. This will foster innovation and inclusivity in the business landscape.
AI can democratise access to technical capabilities, allowing non-experts to utilise sophisticated tools and algorithms. Natural Language Processing (NLP) interfaces can enable users to interact with complex systems using everyday language, reducing the need for technical expertise. This empowers citizens to control their requirements directly, while freeing up technical experts to focus on more innovative initiatives for the business.
AI will revolutionise how businesses address unfulfilled requirements by AI expanding their capacity to analyse, adapt and innovate.
