Author:
Harshul Asnani
President - Technology and Media Business, Tech Mahindra

We are living in an era that is predominantly re-defined by artificial intelligence (AI) and generative AI (GenAI). As these technologies become more sophisticated, their impact on industries like communications, high tech, telecommunications, media, and entertainment will be nothing short of transformative. Unlike other comparatively laggard sectors, enterprises from these industries have never shied away from embracing and adapting to next-gen technologies, driven by user demands and trends.

Within the telecommunications industry, AI is playing a pivotal role in optimizing network management, enhancing security protocols, and enabling the deployment of advanced communication technologies. This has facilitated the development of smarter and more efficient networks, leading to improved connectivity, reduced latency, and enhanced overall user experience. In media, alongside the quick adoption of virtual and augmented reality (VR/AR) to deliver immersive experiences in gaming, movies, live events, and even television, AI has helped not only streamline content creation processes but also enhance content personalization. There is a significant shift towards more targeted and relevant content delivery, be it through automated content curation, AI-generated news articles, and more. In communications, the integration of AI-powered chatbots, natural language processing (NLP), and sentiment analysis has also helped these companies offer personalized customer services—ensuring seamless and enhanced engaging experiences.

Defining a Grounded AI-enabled Enterprise Strategy

We must note here that AI is still an emerging technology and there are concerns around ethical usage, data quality control, skill requirements, copyright, and legal issues that organizations need to address more proactively. However, Generative AI is emerging multifold faster than all the technologies so far with a significant impact in a short amount of time. While speed is important but will also require a more focused, grounded approach to their digital strategy, wherein the integration of AI within the workflows and processes does not simply disrupt but also improves business outcomes.

  • What is your goal? Is it to augment your operational processes? Do you have the right datasets that will help train accurate AI models? Are there gaps in your data collection method? Do you have enough quality data to train the models accurately? When you identify the exact areas of improvement, AI can be a strategic partner in your larger business strategy to help you achieve your goals.
  • Are your AI tools aligned to your use cases? Have you established milestones that can help you measure the efficacy of the AI implementation? It is important to monitor, test, and refine the AI algorithms and models repeatedly to improve their accuracy and ensure optimal results for the business.
  • Have you developed in-house skills to navigate your AI strategy? While this technology will be useful for taking on time-consuming data processing and analysis, you will still need to invest in human expertise to navigate the big picture and adapt during events that are beyond your control like market and audience changes, geopolitical issues, and natural disasters.
  • Do you have a robust AI governance model? While AI can be utilized as gatekeepers to filter out harmful, inappropriate data or misinformation, remove inconsistencies or redundancies in processes, and improve overall operations, in the wrong or ignorant hands, this tool can also be misused. It is a tricky balancing act that organizations must be cognizant of when leveraging AI. A strong governance model around AI’s responsible usage can help retain and even enhance trust within the organization as well as across communities. Do you have governance processes in place to periodically validate the compliance of the models for accuracy, ethical, and legal aspects? Models can drift, especially the reinforcement models with minimal to no human interference. It’s important to reflect on the mechanisms in place to detect model drifts and correct them.

Laying the Foundation for an AI-led Value Chain

It’s hard to ignore AI and its influence in our world today. From a public adoption perspective, AI alongside AR/VR has already enhanced content production and creative outcomes, and with time, this technology will lay the foundation of an AI-led value chain within every enterprise.

Imagine a future where products, ads, and information can be shared with end users through tailored interactions based on their immediate wants and needs. Think of being able to go to the movies and adjust the narrative based on viewer sentiment. Picture a sportsground right in the living room of our homes, seamlessly blending the physical and the digital worlds. No wonder, AI has found such quick acceptance across various consumer segments.

And with the further evolution of AI and GenAI, organizations will need to keep exploring new opportunities for value creation, operational efficiency, driving revenue, and revolutionizing customer satisfaction and experiences, ultimately reshaping the future of these interconnected and diverse industries.

About the Author:

Harshul Asnani
President - Technology and Media Business, Tech Mahindra

Harshul Asnani is President - Technology and Media Business at Tech Mahindra. With over 25 years in the technology industry, Harshul is a seasoned leader known for steering high performance global teams and scaling businesses. Based in the San Francisco Bay Area, he is an active board member and is dedicated to mentoring startups and pushing the boundaries on digital transformation. Harshul holds degrees in mechanical engineering and business administration, in addition to completing the management development program from Harvard.