New Accenture study, 79% of Indian organizations report that their investments in automation and generative AI have met or exceeded their objectives, and 64% say they intend to step up their efforts and further develop these capabilities by 2026.
The proportion of businesses worldwide that have fully modernized, AI-led processes and achieved intelligent operations has almost quadrupled from 9% in 2023 to 16% in 2024, according to the report “Reinventing Enterprise Operations with Gen AI.” These organizations outperform their peers in terms of revenue growth, productivity, and scaling generative Artificial intelligence use cases by 2.5x, 2.4x, and 3.3x, respectively. The study’s main finding is that, in India, the proportion of businesses with fully modernized, AI-led operations and processes has increased thrice, from 8% in 2023 to 25% in 2024.
Additionally, it was determined that these “reinvention-ready” businesses are accelerating and increasing the influence of generative Artificial intelligence throughout the organization. In India, these businesses have already created generative Artificial intelligence use cases in customer service (63%), IT & security (65%), finance (76%), and other key areas, all made possible by a digital core.
The majority of businesses, 64% worldwide and 58% in India, still find it difficult to alter their operations, even if the study shows that some are reinvention-ready—moving to the highest level of operations readiness. There are universal explanations for this.
- Globally, organisations lag behind on building a robust data foundation. For example:
70% of respondents say it is difficult to scale initiatives that require proprietary data
61% say their data assets are not yet suitable for generative Artificial intelligence.
- Across the world, the deep dependency on people is often overlooked:
Eighty-two percent of businesses in the early stages of operations preparedness have not implemented a talent reinvention strategy, made plans to address workforce demands, hired new personnel, or provided training to get employees ready for workflows driven by generative AI.
Indeed, 78 percent of CEOs say that their organisation’s training efforts cannot keep up with the rapid advancements in Artificial intelligence and generative AI.
An Accenture poll of 2,000 executives from 12 countries and 15 industries produced the results. Among them were 200 senior executives (81 percent CXOs) from Indian-based businesses.
“Most executives understand the urgency of reinventing with generative AI, but in many cases their enterprise operations are not ready to support large scale transformation,” said Arundhati Chakraborty, group chief executive of Accenture Operations. “Generative AI is more than the technology. It is a driver of a mindset change that impacts the entire enterprise. It requires organisations to have a strong digital core, data strategy and a well-defined roadmap to change the way they operate. Additionally, an end-to-end perspective leveraging talent, leading practices and effective collaboration between business and technology teams is essential for intelligent operations.”
The report highlights four key actions business leaders should take to advance their operations maturity:
Implement a centralised data governance and domain-centric approach to data modernisation.
Make sure that people understand how to create, handle, and consume data by connecting processes and tools across functions. Data should be formatted in a consistent manner so that AI tools can access it throughout the company.
Embrace a talent-first reinvention strategy.
To get a clear picture of where generative AI may most effectively serve consumers, support people, and achieve corporate objectives, reimagine work and reinvent entire workflows.
Ensure business and tech teams co-own reinvention.
Since both teams jointly own how assets, platforms, and solutions are produced to fully utilise the enterprise-wide potential of generative AI, collaboration fosters innovation.
Adopt leading processes to drive business outcomes.
To visualise process gaps and gain a clear understanding of operational inefficiencies or areas for improvement, use cloud-based process mining to calibrate internal and external benchmarks.
Also read: Viksit Workforce for a Viksit Bharat
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