The Power of AI and Cloud – Evolution meets Convergence
Balakrishna (Bali) D.R., Executive VP, Head of AI and Automation Services, Infosys, explores the drivers of change in AI and Cloud and how it is impacting enterprise strategic development in an interview with Dr. Sally Eaves, a highly experienced chief technology officer, professor in advanced technologies, and a Global Strategic Advisor on digital transformation.
The Role and Adoption of AI has Changed
As many of us pause to reflect on the trends set to dominate 2022, it is clear that we have entered an Age of Convergence across technologies notably AI, Cloud, 5G, and IoT, and similarly, an Age of Experience too, where increasingly personalized expectations from consumer to employee have never been higher.
The pandemic clearly catalyzed acute disruption across sectors and across the world, accelerating digital transformation and adoption levels by up to a staggering seven years (McKinsey). The results of digitalization have largely shown the significant payoffs from that investment, further accelerating enterprise interest and influencing many businesses’ long-term digital strategies, especially around Artificial Intelligence. Infosys exemplifies this sustained commitment, having embedded AI into every area of the company and most notably training, legal, finance, and cybersecurity, whilst also continuing to evolve its offerings to customers to align with their changing behaviors, needs, and expectations. Speaking with Bali, seven drivers of change came to the fore:
- Innovation in cloud-based services and computing power to better leverage AI and Data Science
- The realization of powerful use cases enabled by integrative technologies with AI at the core
- The pivotal role of AI and other technologies to manage the pandemic like contract tracing and creation of vaccination
- Enhanced accessibility and democratization including ‘AI As-A-Service models’, advances in AI training, and rise in Open AI/APIs
- Regulation starting to catch up with AI development including guideline collaborations
- Increasing resonance of AI being a force for societal good has helped to ‘change the narrative’
AI and Cloud - Reimagining Experiences
Multi-channel and omnichannel are not the same thing! People expect seamlessness of experience across web, mobile and social apps alike and increasingly expect the same personalization of experience obtainable in their personal and consumer lives to be available in their working ones too, notably in productivity tools. Putting this into context, AI and appropriate technology integrations can now permeate and enhance every aspect of the consumer journey, from personalized demand generation, providing a curated set of products that fits the customer profile to enabling a frictionless purchasing process. AI can help engage with the customer in the right channels, at the right time, in the right way - from Virtual Agents to AR - and all the way through to affording the services for additional product supply post-sale. And for employees, there is a similar re-imagining occurring across the journey of hiring, onboarding, training, team integration, and organizational engagement. A great example of this change is undertaken within Infosys itself in relation to its talent management lifecycle, improving efficiency across its recruitment process.
‘We use AI to predict the demand, what kind of skills will be in demand, and the quantity of demand …. and to screen, process and review more than 2 million resumes a year and even to understand the speaking skills, tone, articulation of the perspective employee [interview process for contact centers] and then in terms of internal training we use something which we call ‘Infosys Digital Brain’ to find skills demand matches… AI also helps us figure out which employees are getting disengaged to predict churn ...and what should we do in terms of interventions’ - Balakrishna (Bali) D.R. Executive VP, Head of AI and Automation Services
Broadening AI Uses and Democratization of Access
It is critical to make AI (and automation more broadly) available to a greater number of users within organizations and beyond traditional heavy technology-facing roles. As discussed with Bali, this starts with education, communication, and values, and I especially love his stated Infosys commitment to ‘invest in each of you’. This changes the narrative around AI potentially taking away jobs to enabling higher-order work activities and indeed opening up new role opportunities too.
As an example, Infosys uses AI within its digital learning platform Lex, an implementation of Wingspan, a next-generation learning solution accessible anytime, anywhere, and on any device to customize programs for both individuals and teams. And the results of increasing AI and automation across the organization have attracted a myriad of collective benefits including efficiency, cost reduction, experience improvement across the entire customer lifecycle, mean time to issue resolution, and even employee morale. This is the value that has been passed onto customers, including setting up specific projects to democratize AI usage into the line of business functions without the need for detailed technical knowledge and experience. The benefits of Infosys’ living labs and information network are also clear, being able to test and iterate with customers to lead into a Proof of Concept and supporting engagements with bleeding-edge start-ups too.
Strategic and Scalable Evolution - Cloud and AI
The trajectory of AI and cloud strategy is interwoven. With cloud the foundational layer for digital transformation from infrastructure, to the services available to clients to transform quickly, AI helps to reduce the complexity of migration processes notably technology refreshes. This may range from the database itself, through to legacy languages, with developers leveraging AI to translate them into modern code thereby expediting the end-to-end development process, improving productivity, and freeing up time for value-added activity such as creative problem-solving. And once migrated, AI helps support the management of operations to optimize ‘Return on Cloud’ by affording visibility and clarity on metrics such as spend and consumption, for example identifying seasonal patterns on load and helping move beyond reactive to a more proactive and always-on active intelligence.
‘We have a platform called Leap - through that we are able to analyze issues before they actually happen, whether it is infrastructure, application-level issues, we are able to respond’ - Balakrishna (Bali) D.R. Executive VP, Head of AI and Automation Services
And in tandem with this, the cloud significantly supports the adoption of AI and API services, especially those available from the hyperscalers, enabling both easier consumption and the capacity to scale AI workloads up and down at speed. Indeed, scalability is a critical part of cloud enablement with many organizations starting to adopt AI in a few use cases or Proofs of Concept but not scaling across their entire entity. A cloud platform-based approach supports this critical ‘moving beyond’ with all the benefits of standardization, curated services, pre-trained models, and lifecycle management too. Clearly AI and cloud feed off each other and where they amplify well they do so both reciprocally and significantly - creating an interlinked strategic focus imperative. This is especially critical when we consider the fact that AI-demand is outpacing supply, fueled by accelerated demands from the pandemic and other resource challenges, and leading to supply chain delays and chip shortages.
Enterprises must therefore optimize their extant resources, which can be supported by the cloud service providers who can pull resources and automate infrastructure to ease AI adoption and enable data centers to be utilized at almost 100% capacity. Infosys Applied AI is an integrative flexible offering that allows businesses to access, deploy, and contextualize cloud services and harnesses the power of convergence across cloud, AI, and analytics to enable new business solutions, manage risks and efficiently scale AI investment enterprise-wide. And as the democratization of AI continues, such an embedded approach to future-proofing technology investment is fast becoming business-critical.
AI for Good and Ecosystem Collaboration
And finally, when we reflect on the future of AI and cloud, one further aspect comes to the fore and that is the shared value benefits their evolution and convergence can bring, further supported by the power of education, research, and partnership. The new Infosys AI Innovation Centre exemplifies this approach, attracting universities, startups, and large enterprises alike with its ready-to-use applications for various industries supported by the combination of Infosys Applied AI, Infosys Cobalt and a depth and breadth ecosystem of digital technologies.
An additional example is the collaboration between Infosys and BP known as ‘Energy As A Service’ and originally announced here. It aims to collect data from multiple energy assets and apply AI to systemically optimize supply and demand for cooling, heating, power, and EV charging. This can help companies maximize their entire energy consumption and utilize more sustainable energy sources. The specifics will vary by industry sector and as highlighted by Bali, the advance of 5G makes an interesting case in point, with AI the key enabler to make connected and efficient choices.
‘We can actually optimize the entire energy consumption [asking ourselves] - When is the peak? When do you need to scale up and scale down the energy requirement in the tower – to know how much coverage you need and how much bandwidth that you have to do based on being able to predict when the load is right. You can look at the whole area around the tower and you can look at how you can use solar panels, wind turbines, etc to be able to generate power to actually run the tower, you can use battery storage to be able to consume the power during the night. And then actually, during peak hours you actually consume from the battery. And that way you reduce the load on the grid’ - Balakrishna (Bali) D.R. Executive VP, Head of AI and Automation Services
This brings to the fore that not only can AI, cloud, and tech convergence more broadly deliver enhanced experiences and new product and service innovations for customers and employees alike, but this integration can also deliver on vital Environmental, Social, and Governance (ESG) outcomes. With consumers and ecosystem stakeholders increasingly conscious and ensuring enterprise transparency, commitment, and accountability for social impact outcomes now a key organizational differentiator, its importance cannot be overstated. Underpinning this, the vision of Global IT Services Leader Infosys in this space is key - aiding enterprise partners to adopt a comprehensive and holistic roadmap approach to scaling AI and ensuring ‘Return on Cloud’, whilst supporting the critical balance of advancing innovation while protecting existing investments at the same time.