The communications, media, and information services (CMI) industry is well-positioned to take advantage of the latest advances in artificial intelligence (AI). Leveraging the power of data, the industry can use AI to create new value chains and even richer ecosystems to drive growth. The TCS AI for Business Study shows that most business leaders in CMI companies are optimistic about the potential of AI. This report sheds light on this topic as well as provides fresh insights into how CMI firms are moving forward to create effective AI strategies for their enterprise. This report explores:
Yet there’s no consensus on AI adoption strategies and not enough metrics to measure success.
62% of corporate functions have AI projects completed or in-process .
30% of corporate functions are planning AI implementations.
54% are more inclined toward using AI for spurring innovation and growth.
When asked what their primary concerns are about AI, especially with the emergence of generative AI (GenAI), five strategic challenges are top of mind for CMI companies:
As the integration of AI into business processes accelerates, measuring the financial return on such an investment becomes increasingly significant. But only 17% of CMI executives said they have "good enough" metrics and KPIs for their current AI deployments.
Without adequate KPIs for AI-enabled operations, proving ROI and getting future buy-in is challenging.
Even in this era of AI, there’s no substitute for human creativity, empathy, and strategic thinking. 64% of CMI companies think human strategic decision-making and creativity will remain essential for competitive advantage.
Most executives believe AI will augment and enhance human capabilities, enabling people to focus on higher-value activities. 44% of CMI companies expect most of their employees will be using GenAI on a daily basis in the next three years.
Innovation and revenue growth will be a focus for future AI implementations. In fact, 54% of CMI Pacesetters—financially overperforming companies in the study—are more focused on using AI to spur innovation.
Prioritize AI use cases through the lens of strategic alignment to business objectives, potential business value and impact, minimized business risk, and cost/effort required to implement, to realize early wins and optimal use of resources.
Setting up a value management office will help to ensure consistent and sustained business value delivery from AI projects.
A value grid helps identify potential business scenarios, across various revenue streams/business functions of the enterprise, where AI can help deliver exponential value.
Explore AI to transform the customer experience across every single touchpoint in their journey to improve CSAT, net promoter score (NPS), and reduce churn.
Capitalize on AI’s capabilities to deliver more personalized, proactive, and valuable experiences differentiating your business from the competition.
Collaborate with partner ecosystems in the areas of accessing specialized expertise and talent, technology and resource sharing and innovation, to accelerate and enhance scaled AI adoption. Strike a balance between building the in-house AI talent and expertise and utilizing specialists from technology partners.
To harness AI responsibly, CMI enterprises need to build an AI governance framework covering fairness and transparency, ethical principles, security and privacy standards, observability, governance and risk management and regional and telecom industry regulatory controls. This ensures AI is used ethically and delivers value for both the organization and the society.
TCS’ Thought Leadership Institute conducted a double-blind study of approximately 1,272 senior executives with P&L responsibilities in 12 industry sectors across Asia, Europe, Nordics, LATAM, North America, and the United Kingdom and Ireland, with respondents having annual revenue of $5 billion to $100 billion. The CMI industry findings are based on feedback from 86 survey respondents.
This global study examines how CEOs, LOBs, directors, and business line managers prepare their businesses to be AI-ready, focusing on aspects such as their strategy around operations, talent, and future implementation plans. The study provides best practice recommendations based on these insights.
