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How AI Can Transform the Online Experience for Engineers

Tools like generative AI can enhance how engineers source new systems and components, but the proper checks and balances must be put in place.

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AI has become one of the defining technologies of our time. Its broad applicability and transformative potential across industries and use cases means it already touches our lives in multiple ways. Programs such as ChatGPT have demonstrated remarkable capabilities in natural language understanding. We also see advancing functionality in text-to-image creation, opening up new possibilities.

Recent research from Gartner shows that 45% of executive leaders say the success of ChatGPT has prompted them to increase AI investments. Some 70% say their organization was investigating and exploring mode the adoption of generative AI.

This rapid development presents opportunities and threats for organizations, large and small. Immediate questions arise. What does the emergence of AI mean for my business? How might it change the dynamics of the organization in terms of offering greater efficiencies or differentiation? And how do we manage its implementation in a safe and ethical way? Each question needs careful consideration, as the head-long rush towards AI adoption can undoubtedly bring problems in its wake.

At RS, we have a well-established innovation model using a sandbox approach where new technologies can be learned, developed and tested in a controlled and monitored environment. That way, we can explore the art of the possible with no risk to our customers, deploying proven platforms that enhance our operations. We have taken this approach with generative AI, and it is already bringing substantial end-user benefits to our digital environments. 

Improving Customer Experiences

So, let us look at how generative AI could transform how products and services are provided to industrial equipment designers, builders and maintainers. Firstly, it is worth noting just how quickly this technology is moving. Using ChatGPT as an example, the shift from version 3.5 to 4 in months saw a sharp increase in accuracy and efficiency, enabling it to understand and respond to more inputs. This momentum is likely to continue with further upgrades in quick succession. 

Also, these generative AI programs are incredibly easy to use, making them accessible for less technically proficient individuals. Essentially, the fear factor has gone. Whereas in the past, AI was a complex subject restricted to specialist roles such as computer science or software, engineering, or advanced medicine, it is now simple for anyone to make a natural language inquiry and see the power of that model. 

Capability and usability are, therefore, critically important. And those factors will increasingly come into play as generative AI continues to make its presence felt online. RS transacts 64% of its revenues through digital channels, and over 70% of our customer inquiries for products and components come through our on-site search capability. So, that is many millions of inquiries a month – most of which are unique. The potential for generative AI to enhance that search function is immense. 

We have already moved to a Google AI-driven platform with natural language processing off long-tail keywords to provide more relevant and accurate results. With customers making highly bespoke inquiries through type, this kind of big data processing allows us to improve user experience significantly.

But where might AI go next? In online environments such as electronic components distributor websites, AI-based technologies could help deliver even more personalized recommendations, 3D visualizations of products, interactive product tours, improved inventory management, or better post-purchasing support. Again, these are possibilities – not necessarily realities – and it will be about continually assessing and evaluating new functionality and only introducing them when proven and ready.

Understanding the 'Three As'

These are examples of how AI might transform the digital world. More generally, the opportunities for generative AI, and indeed AI in its broader definition, can be categorized for simplicity under the 'three As.' 

Firstly, there is automation. How can it be used to help automate non-value processes so that you can redeploy human resources to more value-added activities? Then there is augmentation. The search example given earlier exemplifies this. As the technology learns more from the content inputs, it personalizes and improves your recommendations - which augments your experience. Finally, there is advancement, where AI will provide transformative breakthroughs, particularly in specialized areas such as research or medicine, where it could profoundly affect the speed of development and performance of new drugs. 

As a technologist and computer scientist by background, I find the AI applications that have yet to be imagined most exciting. As algorithms and models get smarter, the deployment options will increase, presenting new opportunities over time. 

Considering Ethics & Privacy

Having offered a positive vision of AI's future, it is essential to acknowledge the challenges and potential dangers that it brings. All organizations must balance their employees' natural curiosity around exciting technologies such as ChatGPT with the realization of limitations. Take the provision of new marketing material as an example. Undoubtedly, generative AI can significantly shorten the time from concept to delivery of a broad range of content, such as catalogs and brochures, that still feature heavily in B2B environments. But guardrails need to be put in place.

The nature of large language models means that information is being scraped from a vast repository of existing data. That brings questions of accuracy, authenticity, privacy and intellectual property into play. So, there are risks and implications, and suitable checks and balances must be in place. Indeed, there must be some caution before AI-generated material enters the mainstream.

Cybersecurity is a consideration, too. As with any technology at the bleeding edge, a lack of usage protocols runs the risk of data breaches and the leaking of sensitive information. With generative AI, for example, prompting could expose facts or figures that could be visible to the large language model's developers or shared with other parties. This oversight represents a risk in a B2B environment where details such as technical specifications could be confidential.

The message, then, is that a balance needs to be struck. It is vital that employees are aware of new technologies, such as generative AI, and encouraged to consider how it could be a force for good. However, factors such as IP, privacy and risk are very real, and the correct security and legalities must be implemented.

Capitalizing on AI

Nicki Young, Chief Digital and Innovation Officer, RS GroupNicki Young, Chief Digital and Innovation Officer, RS GroupRS GroupAI represents a tremendously exciting technology that will continue to impact our sector significantly. At RS, we have incredibly talented people (scientists, engineers, designers and product teams) looking at the continued advancement of our products and services and how we can bring superior value to our customers and suppliers. This progression is a continued journey, and AI will remain an invaluable tool in connecting new and different technologies across our domain. 

We also have a broad ecosystem of partners and brands who are genuine leaders in their collective fields. And AI brings the opportunity for even closer partnerships and collaboration with those organizations to underpin the innovations of tomorrow. 

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