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AI adoption now part of performance metric for tech-product firms

Indian companies to take time to adopt

Atal Innovation Mission, artificial intelligence
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Palo Alto Networks is linking AI adoption to performance reviews, signalling a broader shift in how tech firms assess talent.

Avik Das Bengaluru

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When cybersecurity major Palo Alto Networks began integrating artificial intelligence (AI) usage into its “performance elevation” process, it sent a clear signal to its workforce: AI is no longer optional. The company made adoption of sanctioned AI coding agents and internal AI-driven tools an organisational priority, encouraging teams to embed them into daily workflows under strict data guardrails.
 
While the shift is currently more visible among global product and consulting firms, industry executives said it might not be long before proficiency in AI tools — and demonstrable productivity gains from them — became a key metric even in India’s $300 billion software services industry.
 
“AI usage is being integrated into the performance elevation process. We use it to encourage usage, coach teams, and share good practices to collectively increase the speed of innovation across teams. Ultimately, we evaluate the collective impact of these tools on our organisation’s ability to deliver cutting-edge solutions faster, rather than measuring AI usage as an isolated individual requirement,” said Kunal Ruvala, senior vice president and general manager of India, Palo Alto. 
 
For its India research and development centre, this shift towards sanctioned AI coding assets and internal AI-driven tools is an organisational imperative for driving productivity. 
 
Palo Alto is not alone. From product firms such as Intuit and Arista Networks to consulting giant Accenture, companies are increasingly factoring AI adoption into employee evaluations — and in some cases, promotions — as they seek measurable returns on rising investments in AI tools.
 
Intuit and Arista Networks did not respond to requests for comment. 
 
With enterprises spending an estimated $4,000–5,000 per employee annually on AI platforms and coding assistants, managements are under pressure to ensure widespread adoption. The message is becoming clearer: employees who fail to meaningfully integrate AI into their work risk falling behind in performance assessments. 
 
Neeti Sharma, CEO of TeamLease Digital, believed the trend would take time to catch up in India. “Not every company has an AI policy governing its usage. It is only the technology and consulting firms that are making it mandatory as they have the necessary infrastructure for it. That too not at all levels but staggered.” 
 
Accenture, the world’s largest IT services company by revenue, told senior staff that they must regularly use its AI tools if they were to be considered for promotions and leadership roles. Associate directors and senior managers at the consultancy firm were informed that “regular adoption” of AI would be required to progress to leadership positions. 
 
In September, Accenture outlined a restructuring strategy that said employees who are unable to reskill on AI would eventually be laid off. TCS, India’s largest IT services company, also laid off about 12,000 people earlier this financial year as it sought to become more agile in an era of AI-led business transformation. 
 
TCS chief executive officer K Krithivasan urged the top brass of his company, at a Nasscom event last week, to build or become obsolete. He cautioned that while the juniors were more proficient in the usage of AI, the senior management was still reading and hearing rather than creating. 
 
However, not all companies have on boarded the idea. Questions remain on how to measure usage of tools and the benchmark against which an employee should be evaluated.
 
UST Global chief operating officer Gilroy Mathew said the company expected employees to use AI as a professional and not as tools for shortcuts. While AI is relevant to performance, there is increasingly an indirect and contextual relevance to AI, which measures the outcomes such as productivity gains, quality improvement, and cycle of production and innovation. 
 
“We respect the performance of each individual and do not treat AI usage as a standard or a mandatory performance metric at this point. Because by measuring success of how many tools someone has used or not by superficial adoption, this is not what we want to be,” he added.