Creating ‘pockets of value’ in the age of GenAI


Stuart Mason
Contributor

Forward-looking business strategies have become more crucial than ever. The year 2023 witnessed a significant breakthrough of generative AI revolution, with the technology truly hitting the mainstream.  

Following the success of large language models like ChatGPT, businesses of all scales, across a range of industries are looking to experiment similar technologies for potential applications within their organisations. 

According to the Infosys Generative AI Radar, the six major countries in APAC spent $1.4 billion on generative AI in 2023, with 55 percent of companies in the region having already implemented a solution.

Businesses having realised that Enterprise AI is hugely different from Consumer AI, companies will embrace AI in a more meaningful way that provides real value to consumers in coming years, Infosys global head of data, analytics and AI, Sunil Senan, said.

The perfect analogy to grasp AI adoption according to Mr Senan is mountaineering – climbing the AI mountain. 

The AI mountain possesses similar calculated risks with the potential for high rewards. Both approaches require careful planning, preparation, having a contingency plan in case of unexpected situations, whether it’s encountering a treacherous weather event on a mountain or encountering the data and ethical challenges during AI implementation. 

The true strength of AI is unleashed only when you choose the right AI fit at the onset, frame and size the right opportunities and quantify potential impact of AI at the onset of any AI initiative which sets the course for success. 

Speaking on the first episode of a two-part podcast series, Advancing Business in the Age of Artificial Intelligence, Mr Senan discussed some early use cases of applying AI for strategic business value, and how to adopt a responsible-by-design approach to mitigate the associated risks.  

According to Mr Senan, some of the industries that are early adopters of generative AI with specific use cases are healthcare, energy, retail, and financial services. The focus is moving from digital-first to AI-first and using this shift to amplify the potential and opportunities that companies have within the industry value chain. 

He specified about the opportunities that data and AI provides to build connected ecosystem for example how healthcare data can connect with CPG companies, insurance companies, and fitness industries.  

Sunil Senan, Infosys’ global head of data, analytics & AI, and InnovationAus.com publisher Corrie McLeod

Senan also expressed his observation that their customers are developing a deeper understanding of the need of a comprehensive strategic framework around this transformation, which does not limit to technology but a holistic AI-first mindset that involves people, culture, and business processes.  

According to the research, Australian companies also demonstrated a higher effectiveness in this adoption process and, importantly, are more cognisant of the technology’s potential impact and the ethics around its use. 

For companies big or small looking to start the process of adopting generative AI solutions, it’s crucial to properly investigate and consider the risks associated with these technologies. 

“Anything done with generative AI is seen through a lens of value creation on one side and responsibility on the other,” he said. 

“This technology provides an unprecedented opportunity to create new pockets of value – and this will generate some risks that need to be managed.” 

Businesses should look to take a responsibility-by-design approach when adopting generative AI offerings, with a focus on trust, ethics, privacy, security and compliance. 

Mr Senan pointed that the data which will be consumed by AI and Gen AI is much broader than the data consumed in the previous wave of digital transformation.  

The foundational aspect of ‘Getting enterprises data ready’ is to get ‘ALL’ data under management, such as user generated data, transactional, Machine data etc. This includes files, emails, websites, software codes, videos, audios, sensor data, IoT data and so on. Currently 80 percent of the world’s data is unmanaged and ungoverned. 

“If you think about emails, you and I can have an email exchange that comprises our opinions, or information that isn’t necessarily true,” he said. 

“If a generative AI model was to be trained with information like this as its foundation, it would propagate a lot of things that are not necessarily true.” 

To get enterprises data ready for AI, Infosys offers a smart data fingerprinting service, which is an autonomous process that fingerprints all of this data and delivers a high-level understanding of what it is and how it should be handled appropriately. This powers the core processes such as data curation, data governance, security/regulatory compliance, Ethics/biases, and consumption governance. 

“We must understand what lies in all of these data oceans that will be processed by AI,” Mr Senan said. 

“This data is noisy and dynamic and can’t possibly be managed with a human workforce.” 

Getting data ready should be the starting point for an organisation looking to adopt generative AI in an efficient and responsible way. To ensure that AI becomes a force for positive change in both the organisation and the world, we must prioritise responsible practices, ensure transparency in its decision-making, and mitigate potential harms.   

There are several layers to this foundation, Mr Senan said, including data quality and governance, regulatory compliance and trust. 

Even after mastering these basics, many organisations are stuck in a cycle of continuous experimentation and more than 90 per cent of PoCs don’t scale. Infosys Innovation at speed and innovation at scale helps organisations to not only bridge this gap and monetise AI-powered innovations but also create entirely new revenue streams. 

While the businesses are advancing in the path of AI the true fulfilment lies in the ethical path we choose to navigate it.  

“Most businesses we work with have been established brands for years or decades,” he said. 

“These brands were established by creating a standard for what they stood for, which often became the inspiration for other brands to follow and communicate a value to their consumers. 

“What we do with generative AI shouldn’t be very different from what those brands were established for – those core principles remain the same.” 

The Advancing Business in the Age of Artificial Intelligence podcast series and accompanying articles are produced by InnovationAus.com in partnership with Infosys. 

Do you know more? Contact James Riley via Email.

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