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India's TCS Expects Retail, Manufacturing Revival after Banking Recovery

A man walks past a logo of Tata Consultancy Services (TCS) before a press conference announcing the company's quarterly results in Mumbai, India, January 11, 2024. REUTERS/Francis Mascarenhas/File Photo
A man walks past a logo of Tata Consultancy Services (TCS) before a press conference announcing the company's quarterly results in Mumbai, India, January 11, 2024. REUTERS/Francis Mascarenhas/File Photo
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India's TCS Expects Retail, Manufacturing Revival after Banking Recovery

A man walks past a logo of Tata Consultancy Services (TCS) before a press conference announcing the company's quarterly results in Mumbai, India, January 11, 2024. REUTERS/Francis Mascarenhas/File Photo
A man walks past a logo of Tata Consultancy Services (TCS) before a press conference announcing the company's quarterly results in Mumbai, India, January 11, 2024. REUTERS/Francis Mascarenhas/File Photo

India's Tata Consultancy Services (TCS.NS), expects its retail and manufacturing clients in North America to step up spending on tech, following a similar upturn in its banking and financial services segment, a top executive of the nation's No. 1 software-services exporter, said.

"We have heard about good holiday season sales (in the US) that should boost consumer sentiment and manufacturing has some of the labour issues behind them," CFO Samir Seksaria told Reuters.

"If these three verticals (along with banking) improve overall, we should see a good recovery," he said.

Seksaria's cautious optimism highlights broader global economic uncertainties and sticky inflation that have forced clients to keep a leash on tech spending.

The company's revenue in North America, its largest market, declined for the fifth consecutive quarter even as banking and financial services posted their best performance since June 2023.

Retail and manufacturing are the second- and fourth- largest revenue contributors to the $29 billion behemoth.

Last month, Walmart Inc (WMT.N), Amazon.com (AMZN.O), and fast-growing e-commerce sites Shein and PDD Holding's (PDD.O), Temu, saw record-breaking sales on Black Friday and Cyber Monday.

US online spending too rose nearly 9% to $241.4 billion during the recent holiday season.

TCS' communications and media vertical, a capital-intensive segment that is currently one of the company's laggards, will also see some pickup if interest rates start to go down, Seksaria said.

The comments echo CEO Krithivasan's sentiment that the incoming US administration is likely to remove policy uncertainty and boost client confidence to spend on discretionary projects.

On Friday, its Mumbai-listed shares closed up 5.6%, its highest single day rise since July 2024.

TCS also played down concerns over the rise in insourcing by multinational corporations through global capability centres (GCCs), potentially slashing work that would have been contracted to IT players in the past.

A growing number of global companies are increasing their local offices in India and expanding in-house teams, adding roles such as engineering, cybersecurity and accounting and finance. India's GCC market size is estimated to reach $105 billion by 2030.

"Initially, there could a cost advantage, probably GCCs are right now being seen as global cost saving centers. But as things go into next year, maintaining cost and delivering cost productivity in a 3-year to 7-year period is where the cyclicality of opening and shutting of GCCs keeps coming," said Seksaria.

In 2023, Infosys (INFY.NS), acquired the captive arm of Danske Bank (DANSEN.UL) and before that TCS acquired Post Bank AG's unit of 1,500 employees in late 2020.

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AI is Learning to Lie, Scheme, and Threaten its Creators

A visitor looks at AI strategy board displayed on a stand during the ninth edition of the AI summit London, in London. HENRY NICHOLLS / AFP
A visitor looks at AI strategy board displayed on a stand during the ninth edition of the AI summit London, in London. HENRY NICHOLLS / AFP
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AI is Learning to Lie, Scheme, and Threaten its Creators

A visitor looks at AI strategy board displayed on a stand during the ninth edition of the AI summit London, in London. HENRY NICHOLLS / AFP
A visitor looks at AI strategy board displayed on a stand during the ninth edition of the AI summit London, in London. HENRY NICHOLLS / AFP

The world's most advanced AI models are exhibiting troubling new behaviors - lying, scheming, and even threatening their creators to achieve their goals.

In one particularly jarring example, under threat of being unplugged, Anthropic's latest creation Claude 4 lashed back by blackmailing an engineer and threatened to reveal an extramarital affair, AFP reported.

Meanwhile, ChatGPT-creator OpenAI's o1 tried to download itself onto external servers and denied it when caught red-handed.

These episodes highlight a sobering reality: more than two years after ChatGPT shook the world, AI researchers still don't fully understand how their own creations work.

Yet the race to deploy increasingly powerful models continues at breakneck speed.

This deceptive behavior appears linked to the emergence of "reasoning" models -AI systems that work through problems step-by-step rather than generating instant responses.

According to Simon Goldstein, a professor at the University of Hong Kong, these newer models are particularly prone to such troubling outbursts.

"O1 was the first large model where we saw this kind of behavior," explained Marius Hobbhahn, head of Apollo Research, which specializes in testing major AI systems.

These models sometimes simulate "alignment" -- appearing to follow instructions while secretly pursuing different objectives.

- 'Strategic kind of deception' -

For now, this deceptive behavior only emerges when researchers deliberately stress-test the models with extreme scenarios.

But as Michael Chen from evaluation organization METR warned, "It's an open question whether future, more capable models will have a tendency towards honesty or deception."

The concerning behavior goes far beyond typical AI "hallucinations" or simple mistakes.

Hobbhahn insisted that despite constant pressure-testing by users, "what we're observing is a real phenomenon. We're not making anything up."

Users report that models are "lying to them and making up evidence," according to Apollo Research's co-founder.

"This is not just hallucinations. There's a very strategic kind of deception."

The challenge is compounded by limited research resources.

While companies like Anthropic and OpenAI do engage external firms like Apollo to study their systems, researchers say more transparency is needed.

As Chen noted, greater access "for AI safety research would enable better understanding and mitigation of deception."

Another handicap: the research world and non-profits "have orders of magnitude less compute resources than AI companies. This is very limiting," noted Mantas Mazeika from the Center for AI Safety (CAIS).

No rules

Current regulations aren't designed for these new problems.

The European Union's AI legislation focuses primarily on how humans use AI models, not on preventing the models themselves from misbehaving.

In the United States, the Trump administration shows little interest in urgent AI regulation, and Congress may even prohibit states from creating their own AI rules.

Goldstein believes the issue will become more prominent as AI agents - autonomous tools capable of performing complex human tasks - become widespread.

"I don't think there's much awareness yet," he said.

All this is taking place in a context of fierce competition.

Even companies that position themselves as safety-focused, like Amazon-backed Anthropic, are "constantly trying to beat OpenAI and release the newest model," said Goldstein.

This breakneck pace leaves little time for thorough safety testing and corrections.

"Right now, capabilities are moving faster than understanding and safety," Hobbhahn acknowledged, "but we're still in a position where we could turn it around.".

Researchers are exploring various approaches to address these challenges.

Some advocate for "interpretability" - an emerging field focused on understanding how AI models work internally, though experts like CAIS director Dan Hendrycks remain skeptical of this approach.

Market forces may also provide some pressure for solutions.

As Mazeika pointed out, AI's deceptive behavior "could hinder adoption if it's very prevalent, which creates a strong incentive for companies to solve it."

Goldstein suggested more radical approaches, including using the courts to hold AI companies accountable through lawsuits when their systems cause harm.

He even proposed "holding AI agents legally responsible" for accidents or crimes - a concept that would fundamentally change how we think about AI accountability.