Federal Reserve Vice Chair for Supervision Michelle Bowman has warned that banks must embrace blockchain technology or risk fading into irrelevance. At the Wyoming Blockchain Symposium on 19 August, she urged banks and regulators to drop caution and embrace innovation.
Bowman highlighted tokenisation as one of the most immediate applications, enabling assets to be transferred digitally without intermediaries or physical movement.
She explained that tokenised systems could cut operational delays, reduce risks, and expand access across large and smaller banks. Regulatory alignment, she added, could accelerate tokenisation from pilots to mainstream adoption.
Fraud prevention was also a key point of her remarks. Bowman said financial institutions face growing threats from scams and identity theft, but argued blockchain could help reduce fraud.
She called for regulators to ensure frameworks support adoption rather than hinder it, framing the technology as a chance for collaboration between the industry and the Fed.
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Indian firms are accelerating the adoption of AI, with many using AI agents to enhance workforce capabilities rather than relying solely on traditional methods.
According to Microsoft’s 2025 Work Trend Index, 93% of leaders in India plan to extend AI integration across their organisations within the next 12 to 18 months.
Frontier firms in India are leading the charge, redesigning operations around collaboration between humans and AI agents instead of following conventional hierarchies.
Over half of leaders already deploy AI to automate workflows and business processes across entire teams, enabling faster and more agile decision-making.
Microsoft notes that AI is becoming a true thought partner, fuelling creativity, accelerating decisions, and redefining teamwork instead of merely supporting routine tasks. Leaders report that embedding AI into daily operations drives measurable improvements in productivity, innovation, and business outcomes.
The findings are part of a global survey of 31,000 participants across 31 countries, highlighting India’s role at the forefront of AI-driven organisational transformation rather than merely following international trends.
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A new MIT study has found that 95% of corporate AI projects fail to deliver returns, mainly due to difficulties integrating them with existing workflows.
The report, ‘The GenAI Divide: State of AI in Business 2025’, examined 300 deployments and interviewed 350 employees. Only 5% of projects generated value, typically when focused on solving a single, clearly defined problem.
Executives often blamed model performance, but researchers pointed to a workforce ‘learning gap’ as the bigger barrier. Many projects faltered because staff were unprepared to adapt processes effectively.
More than half of GenAI budgets were allocated to sales and marketing, yet the most substantial returns came from automating back-office tasks, such as reducing agency costs and streamlining roles.
The study also found that tools purchased from specialised vendors were nearly twice as successful as in-house systems, with success rates of 67% compared to 33%.
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The Commonwealth Bank of Australia has reversed plans to cut 45 customer service roles following union pressure over the use of AI in its call centres.
The Finance Sector Union argued that CBA was not transparent about call volumes, taking the case to the Workplace Relations Tribunal. Staff reported rising workloads despite claims that the bank’s voice bot reduced calls by 2,000 weekly.
CBA admitted its redundancy assessment was flawed, stating that it had not fully considered the business needs. Impacted employees are being offered the option to remain in their current roles, relocate within the firm, or depart.
The Bank of Australia apologised and pledged to review internal processes. Chief executive Matt Comyn has promoted AI adoption, including a new partnership with OpenAI, but the union called the reversal a ‘massive win’ for workers.
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Meta has frozen hiring in its AI division, halting a spree that had drawn top researchers with lucrative offers. The company described the pause as basic organisational planning, aimed at building a more stable structure for its superintelligence ambitions.
The freeze, first reported by the Wall Street Journal, began last week and prevents employees in the unit from transferring to other teams. Its duration has not been communicated, and Meta declined to comment on the number of hires already made.
The decision follows growing tensions inside the newly created Superintelligence Labs, where long-serving researchers have voiced concerns over disparities in pay and recognition compared with recruits.
Alexandr Wang, who leads the division, recently told staff that superintelligence is approaching and that significant changes are necessary to prepare. His email outlined Meta’s most significant reorganisation of its AI efforts.
The pause also comes amid investor scrutiny, as analysts warn that heavy reliance on stock-based compensation to attract talent could fuel innovation or dilute shareholder value without precise results.
Despite these concerns, Meta’s stock has risen by about 28% since the start of the year, reflecting continued investor confidence in the company’s long-term prospects.
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Communication, empathy, and judgment were dismissed for years as ‘soft skills‘, sidelined while technical expertise dominated training and promotion. A new perspective argues that these human competencies are fundamental to resilience and transformation.
Researchers and practitioners emphasise that AI can expedite decision-making but cannot replace human judgment, trust, or narrative. Failures in leadership often stem from a lack of human capacity rather than technical gaps.
Redefining skills like decision-making, adaptability, and emotional intelligence as measurable behaviours helps organisations train and evaluate leaders effectively. Embedding these human disciplines ensures transformation holds under pressure and uncertainty.
Career and cultures are strengthened when leaders are assessed on their ability to build trust, resolve conflicts, and influence through storytelling. Without funding the human core alongside technical skills, strategies collapse, and talent disengages.
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Chief of Microsoft AI, Mustafa Suleyman, has urged AI firms to stop suggesting their models are conscious, warning of growing risks from unhealthy human attachments to AI systems.
In a blog post, he described the phenomenon as Seemingly Conscious AI, where models mimic human responses convincingly enough to give users the illusion of feeling and thought. He cautioned that this could fuel AI rights, welfare, or citizenship advocacy.
Suleyman stressed that such beliefs could emerge even among people without prior mental health issues. He called on the industry to develop guardrails that prevent or counter perceptions of AI consciousness.
AI companions, a fast-growing product category, were highlighted as requiring urgent safeguards. Microsoft AI chief’s comments follow recent controversies, including OpenAI’s decision to temporarily deprecate GPT-4o, which drew protests from users emotionally attached to the model.
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Meta is launching a research lab focused on superintelligence, led by Scale AI founder Alexandr Wang, in an attempt to regain ground in the global AI race.
Mark Zuckerberg is reportedly in talks to invest billions into Scale, reflecting strong confidence in Wang’s data-driven approach and industry influence.
While Meta’s past efforts with its Llama models gained traction, its latest release, Llama 4, failed to meet expectations and drew criticism.
Wang’s appointment arrives during an ongoing talent exodus from Meta, with several senior AI researchers departing for rivals or founding startups.
The new lab is separate from Meta’s existing FAIR division, led by Yann LeCun, who has dismissed the idea of chasing superintelligence. Meta’s partnership with Scale mirrors deals by Microsoft, Amazon, and Google, aiming to secure top AI talent without formal acquisitions.
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Databricks has secured a fresh funding round that pushes its valuation beyond $100bn, cementing its place among the world’s most valuable private tech firms. The Series K deal marks a sharp rise from the company’s $62bn figure in late 2024 and underscores investor confidence in its long-term AI strategy.
The new capital will accelerate Databricks’ global expansion, fuel acquisitions in the AI space, and support product innovation. Upcoming launches include Agent Bricks, a platform for enterprise-grade AI agents, and Lakebase, a new operational database that extends the company’s ecosystem.
Chief executive Ali Ghodsi said the round was oversubscribed, reflecting strong investor demand. He emphasised that businesses can leverage enterprise data to create secure AI apps and agents, noting that this momentum supports Databricks’ growth across 15,000 customers.
The company has also expanded its role in the broader AI ecosystem through partnerships with Microsoft, Google Cloud, Anthropic, SAP, and Palantir. Last year, it opened a European headquarters in London to cement the UK as a key market and strengthen ties with global enterprises.
Databricks has avoided confirming an IPO timeline, though Ghodsi told CNBC that investor appetite surged after fintech Figma’s listing. With Klarna now eyeing a return to New York, Databricks’ soaring valuation highlights how leading AI firms continue to attract capital even as market conditions shift.
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US quantum computing firm Strangeworks has expanded its European presence by acquiring German company Quantagonia. The merger allows organisations to tackle complex planning and optimisation using classical, hybrid, quantum, and quantum-inspired technologies.
Quantagonia, founded in 2021, develops AI-powered, quantum-ready planning tools that combine optimisation, AI, and natural language interfaces. The technology enables experts and non-technical users to solve problems across industries, including life sciences, finance, energy, and logistics.
The acquisition removes barriers to advanced decision-making and opens new go-to-market opportunities in previously underserved sectors.
The combined entity will merge Quantagonia’s solver engine and AI decision-making tools with Strangeworks’ AI and quantum infrastructure. The approach lets enterprises run multiple solvers in parallel and solve problems using natural language without technical expertise.
Strangeworks has strengthened its strategic European foothold, adding to its recent expansion in India and existing operations in the US and APAC. Executives said the merger boosts global growth and broadens access to sophisticated optimisation tools.
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