Despite the momentum, corporate adoption of artificial Intelligence (AI) technologies is still lagging. Indeed, enterprises are recognizing AI’s business implications, but being nascent in business settings, it becomes challenging for them to profitably employ it. In a recent interaction with TTM, Balakrishna D R, Head of AI and Automation, Infosys shares his perspectives on how businesses can embrace AI for business growth and innovation and the unprecedented value AI can bring to the enterprise.
TTM: From an industry point of view, how do businesses know if they are ready for AI?
Balakrishna D R: The only prerequisite for a business venturing into AI is to be prepared for change. AI has applicability in almost every industry. Earlier, one of the biggest barriers was lack of data. However, with the emergence of techniques such as transfer learning and meta-learning, the need for high volume data has reduced. Aspects like explainability of AI, elimination of bias and ensuring AI is used ethically are becoming mainstream, thereby encouraging enterprises to adopt AI more widely. Additionally, today we can automate the steps and processes involved in the life cycle of creating, deploying, managing, and operating AI models. In turn, this can help scale AI more widely into the enterprise.
TTM: Talent crunch is a key challenge in the AI space. How are industry leaders like Infosys solving this problem?
Balakrishna D R: Lack of talent in AI related skills has been found to be one of the top three barriers in almost all surveys. Fortunately, across the globe large investments are being made on training to build AI skills. As the entire experience of corporate training is evolving with the rise of digitization, innovation and the demand for lifelong learning, enterprises are being compelled to invest in next-gen learning environments, digital platforms and innovative learning experiences. When designing learning programs, organizations should ask themselves three main questions:
- What skills are core to working with AI?
- What progression do they seek from today to tomorrow?
- What do they need to be ready for the future?
At Infosys, we have answered the above questions with respect to all the technologies we work with. We have sourced and created in-house material on our learning platform (Lex) that is open to all employees. We have made learning convenient and relevant with real-life, best-in-class curated content in safe practice environments.
We have accelerated our talent transformation journey by categorizing all skills into three horizons. Horizon 1 includes all core services with previous skills that are increasingly being replaced by extreme automation. Horizon 2 includes skills that meet today’s need for new services. Horizon 3 is the skills of the future that underpin our engines of growth. Then, we designed training programs that allow our employees to up skill from Horizon 1 to 2 and 3. These higher skills pertain to not only AI but all innovative technologies such as data science, machine learning, autonomous technologies, big data and analytics, cloud technologies, agile, and DevOps.
Presently, most people have a certain depth and breadth of skills, represented by the figure ‘T’. In future, this will shift to a Z-shaped skill model that will combine business and digital literacy along with five Cs, namely, collaboration, critical thinking, communication, cultural fluency, and change management. We are working with various academic institutions such as Rhode Island School of Design, Purdue university, Trinity College, Hartford, Cornell University and the University of North Carolina to reskill our employee in various digital skills.
TTM: What are some of the other concerns faced by businesses around AI technologies in the country?
Balakrishna D R: We already spoke about the lack of data and skills shortage. Some of the other challenges are lack of a clear strategy and functional silos within the organization. As per a Mckinsey study, just 17 percent of respondents said their companies have mapped out where all potential AI opportunities across the organization lie. Also, only 18 percent have a clear strategy in place for sourcing the data that enables AI work. There is also a reluctance to accept the changes that AI technologies bring across job functions. To adopt AI seamlessly, organizations need to take additional measures to ensure better security, governance, and change management.
TTM: What are the possible business use cases of AI-ML you foresee in the next 3-4 years?
Balakrishna D R: As enterprises can mitigate the challenges around AI adoption, we can see a plethora of new applications and use-cases opening up across industries. Let’s highlight some industry-specific use-cases:
In the financial services industry, AI can play a role in data extraction, data validation, breach detection, and customer risk profiling. In banking, AI finds application in areas such as fraud detection, anti-money laundering, regulatory reporting, document extraction, payment reminder follow-ups, real-time user authentication. Likewise, the insurance industry can benefit greatly from AI, especially in areas such as claim data extraction, claim management, regulatory compliance, risk evaluation, adjudication, match to issued policy.
Again, AI can help streamline distributed marketplaces, food auditing, inventory control, loyalty programs, procurement optimization, and drive supply chain traceability.
On the media and telecom front, AI can help significantly enhance network operations and improve fraud detection, predictive maintenance, and customer service. In the services and utilities industries, AI can help achieve better load forecasting, demand management, predictive maintenance, energy trading, consumption insights, and analysis.
In addition to these industry-specific applications, there are plenty of use cases such as customer service, finance and accounting, HR, marketing and sales, and procurement. For instance, AI can help streamline customer enquiry routing, offer customer self-service support in the form of chatbots or voice assistants, and run customer feedback and surveys. AI can support the HR team through resume screening, candidate profiling, performance management, and employee virtual assistant.
The marketing and sales function can benefit from AI in areas such as price optimization, shelf audits, social media marketing, lead management, and customer data management. In procurement, AI can enable better demand forecasting, payment processing, goods receipt and confirmation, e-auctions, and contract management.
AI Generative Algorithms will transform several creative domains like art, ad design, creating recipes, music generation etc. over the next few years. Doctors powered by AI can diagnose diseases like cancer much faster, virtual nurse assistants can help the elderly. Precision medicine driven by personal genomes and analytics will transform healthcare dramatically. AI based Self-driving trucks, Intelligent warehousing and smart traffic management will transform logistics. The list is just endless.
TTM: What’s your view on who should lead the AI initiatives in an organization – the CEO or the CIO?
Balakrishna D R: I believe an AI initiative should not be seen as a technology upgrade or an IT program but rather as a business strategy. Therefore, it should not be limited to the function of a title. Anyone who has the vision to understand the business value that AI brings and has the necessary command to drive change can lead an AI initiative. The key is to visualize the power of technology and have the conviction that its disrupting. Without such conviction, AI will remain yet another IT project.
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