Bridging the gap between the implementation of Artificial Intelligence (AI) and the delivery of real business value is a common challenge, and one that often prevents companies from engaging with emerging technologies.
However, such technologies – including chatbots, Machine Learning (ML) models and AI-powered Customer Relationship Management systems – have the potential to transform business operations, enhance customer experience and optimise digital performance.
The success rate of AI applications is varied across companies and sectors, but a Deep Learning revolution is under way – with computing power increasing exponentially and algorithms becoming more efficient each day. The capabilities of these technologies are endless; it is more about identifying the right use.
As well supervised learning systems, which most people experience every day when interacting with smart assistants, we now have Auto Machine Learning (Auto ML) models which directly interact with and improve the lives of end users. For example, the smart cane developed by WeWALK to help visually impaired users detect obstacles.
Generative Adversarial Networks are another example. These can be used in retail to digitally show consumers what a make-up product or an outfit might look like on them – a sort of virtual “try-on” experience that improves the user experience, enables engagement and encourages sales conversions.
Developed in line with Quality Assurance (QA) standards and software testing methods, AI systems are evolving constantly and expanding the real-world possibilities in terms of implementation. And in many areas AI is generating impressive results.
Look at Natural Language Processing, where next-generation chatbots are much more receptive, accurate and customer-friendly. Moreover, bots are being utilised to tackle real-world problems commonly thought of as being difficult to automate, including testing functionality, usability, accessibility, trustworthiness of video streaming and gameplay.
The GPT-3 model from OpenAI demonstrates further advancement in this space. As the largest language model created, it has the potential to change not only how we program software but how we interact with machines.
Another area where AI is making significant progress concerns its ability to be culturally sensitive. In fact, some models are being applied to audience and culture research to help deliver hyper-personalised marketing using first-party data.
Undoubtedly, there’s a great deal of research and development still needed in terms of the real-world application of AI on a wider scale, but models are currently being put to good use in a range of industries. The secret to success as we move forward will remain the same: overcoming the obstacles to, identifying the right uses for and ensuring high-quality development of AI.
Learn more at our Quest for Quality conference
If you want to find out more about how AI could deliver benefits for you or your organisation, register for this year’s Quest for Quality conference, hosted by Comtrade Digital Services and taking place online on October 27 and 28. The event will bring together thought leaders and industry professionals from the technology field to discuss the impact, use and advancement of AI.
Keynote speakers include Tariq King, chief scientist at Test.AI; Davar Ardalan, founder and storyteller-in-chief at IVOW AI; Rene Schulte, director of global innovation in Valorem Reply; Miha Röthl, principal big data technology lead for Vodafone Ireland; and Shama Ugale, QA consultant for Thoughtworks.
For more information or to register your attendance, visit the Quest for Quality website: https://www.questforquality.eu