Opportunities for generic AI far outweigh challenges for India

To start with the basics, Zen AI refers to computer models that mine data sets and interpret content including text (ChatGPT), images (Del-e, Stable Diffusion), and audio (AIPA, DeepGram, Assembly AI). Uses artificial neural network to generate. , General AI has been used to automate tasks such as simple customer-service conversations; to speed up tasks, such as document summarization; and enhancing human capabilities such as software coding. From banking and pharma to retail, fashion and (of course) technology, interest and investment is growing rapidly. And its potential is enormous: McKinsey estimates that general AI could add $2.6 trillion to $4.4 trillion annually to the global economy in the form of increased productivity.

What does this mean for India? Given our already strong position as a technology services provider, excellence in General AI can open a new frontier in innovation and entrepreneurship. Overall, we believe it can add over $100 billion in value to the Indian economy.

Given the breadth of potential applications of General AI, businesses that want to start should establish cross-functional groups to coordinate their approaches. These teams will be responsible for training, technology development and establishing new partnerships if necessary. Most importantly, they need to balance the risks of next-generation AI with the value to be created.

There are many ways in which India can profitably harness Next Generation AI. Here are five of them.

Sales Productivity: While digital channels are growing rapidly, channels driven by people such as call centers and stores are still dominant in India. Valuable consumer data is embedded in e-mails, chats, pictures, call recordings and other sources, but traditional machine learning models haven’t detected them. General AI tools can sift through and deploy this data in new ways. For example, equipped with easy access to information on product portfolios, sales staff can make intelligent suggestions to consumers while managers can improve their coaching. It is relevant to many sectors including consumer products, retail, banking, insurance, automotive, building materials and pharmaceuticals.

Similarly, Zen AI tools can help business-to-business (B2B) sales teams improve their productivity by helping them review proposals, write new ones, and spot areas that need attention. .

Customer Engagement: By enabling digital self-service and enhancing agent skills, General AI can improve productivity in this area by 30-45%. For example, it can help lead to less-experienced agents faster, and thus provide stronger customer service. Furthermore, General AI tools can provide a comprehensive overview of past customer interactions; real-time assessment of customer sentiment; and personalized recommendations. It can also spot customer problems and indicate where communications can be targeted. And it can do all this quickly. The potential result is better customer loyalty.

Technology Services: Over the past decade, automation productivity in India has grown by 8-10% per year. General AI can do even better and faster. General AI can handle multiple programming languages; The tools are also easy to deploy, require limited setup and training, and are intuitive to use. In controlled pilot tests, General AI technology tools have provided 25–50% productivity improvements in development, documentation, and testing. The prospects are therefore significant for digital enterprises, software as a service companies and in-house software development teams. Ultimately, General AI can help define innovative offerings for businesses and customers.

Business functions: General AI can support functions such as finance, personnel, procurement, technical support and legal by answering questions based on existing policies, summarizing documents, drafting and reviewing contracts. Early results from such projects indicate a potential for 20-30% improvement in productivity.

Learning effectiveness: General AI tools can provide coaching support to learners from kindergarten to the workplace, whether by offering content, conducting assessments or making tailored recommendations for further learning. In addition to technical skills, it can enable tools for soft skills training such as communication, helping early tenure and low-skilled workers perform better, faster. It could also revolutionize schooling in settings where there are not enough quality teachers; Gen AI tools can act as virtual assistants that support students and notify human teachers when they need attention. In healthcare, they can play a similar role.

In short, Gen AI will likely find applications in all domains and unlock significant new opportunities. However, there will also be challenges. General AI models are prone to ‘hallucinations’ – providing responses that may seem believable but are wrong. There is a need to focus on security, as well as data and intellectual property protection. The financial cost of use and the environmental cost of development can be high. Like any other new development, General AI needs to be managed with organization systems and culture for digital trust and responsible use of AI.

There is also concern that Gen AI’s ability to improve productivity could affect employment in areas such as software development and call centers. Mass adoption of Gen AI for value creation is most likely to occur in organizations and societies that train people in new skills and then match them with new roles, including areas emerging from Gen AI applications .

India is a global leader in technology services and entrepreneurship. The generation leading AI adoption provides a path to strengthen its position and create new opportunities.

Rajat Dhawan, Satya Prathipati and Ankur Puri are Managing Partner, Senior Partner and Partner, respectively, at McKinsey & Company India.