Even as generative AI and broader AI implementation offer numerous benefits in terms of reducing cost and boosting revenues in the long term, several organisations are still hesitant to embrace these technologies, according to Tata Consultancy Services (TCS).
The primary concerns relate to the accuracy of AI predictions, the high cost of implementation, and the complexities involved in integrating these systems with existing business processes.
Businesses are particularly cautious about investing heavily in this evolving technology as it might not deliver the expected return on investment. It could disrupt existing workflows without sufficient benefits as the technology, especially GenAI, is only now stepping out of its experimentation phase, Krishna Mohan, vice president & deputy head, AI.Cloud Unit at TCS, told FE.
“The cost definitely is one aspect of it. But when you integrate and implement it at enterprise scale, you need to look at the performance, you need to look at the security, you need to look at the accuracy, you need to remove the biases. And can it deliver when you integrate in the real-life production system? So I think that’s why it’s an evolving space,” Mohan said.
Revenue improvements and cost efficiency
A recent report by the company, titled TCS AI for Business Study, showed only 19% of about 1,300 CEOs have “good enough” metrics for their current stage of AI deployment.
Yet, an overwhelming 86% of senior business leaders believe AI can significantly improve revenue streams. According to Mohan, “Majority of the customers that we spoke to, 1,300-plus CEOs and others, definitely see the actual role of AI in reimagining business models and driving business efficiencies… So a lot of the projects are predominantly on boosting revenues, improving cash flows”.
The areas where AI has proven particularly effective include predictive analytics for customer behaviour, supply chain optimisation, and even complex tasks like drug discovery, he added. In sectors like customer service, AI-powered chatbots and virtual assistants are already making an impact by improving response times and customer satisfaction.
In manufacturing, AI is used for predictive maintenance of equipment, helping to avoid downtime and reduce repair costs.
But this also means that the impact of AI and GenAI extends beyond just financial metrics, where it will affect the current job structure and sector-specific roles which will lead to some jobs displacement. However, it will also create new roles, particularly in areas around AI, he added.
Driving cloud adoption
The adoption of GenAI is driving businesses towards the cloud, Mohan said. The ease of accessing and processing vast data sets in the cloud makes it a must have technology for AI.
“Generative AI definitely needs your data… The best part of generative AI is that you don’t need to have the data structure. It can even read the unstructured data… So definitely that’s driving more and more cloud and majority of these models… are quite interconnected,” he said.
