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Indian Companies Bullish on Long-Term AI Investments; 76% Surveyed Firms Achieved ROI-Driven Results: IBM Study - Related to investments;, ibm, says, companies, access

Indian Companies Bullish on Long-Term AI Investments; 76% Surveyed Firms Achieved ROI-Driven Results: IBM Study

Indian Companies Bullish on Long-Term AI Investments; 76% Surveyed Firms Achieved ROI-Driven Results: IBM Study

A research study commissioned by computing giant IBM revealed on Wednesday that most Indian companies made significant progress in executing their AI strategies last year.

The study surveyed over 2,000 IT decision-makers worldwide, 224 of whom were from India. Among the ones surveyed in the country, 87% reported progress in their AI strategy, and 76% revealed that they had achieved results driven by return on investment (ROI).

About 89% of the Indian respondents expressed their companies have started more than 10 AI pilots in the last year. Furthermore, 93% of the Indian respondents expressed they will increase their AI investments this year.

The majority of them reported looking for open-source solutions, and 48% revealed that more than half of the AI solutions being used are based on open-source technologies.

Among the companies that are yet to achieve ROI-driven results from AI projects, 33% expect to see savings within the next 12 months, and all of them believe they will achieve a positive ROI within three years.

Only 1% of the surveyed Indian respondents revealed that their AI strategy had not made progress.

The surveyed Indian companies revealed that they are focusing their AI investments this year on IT operations, software coding, and data quality management.

The detailed study from IBM, outlining the findings from multiple countries worldwide, can be found here.

Indian Prime Minister Narendra Modi on Tuesday spoke at the AI Action Summit in Paris, where he expressed that India leads in AI adoption. , India has one of the world’s largest AI talent pools.

“India is building its own large language model. Considering our diversity, we also have a unique public-private partnership model for pooling resources like computing power,” he added. In this year’s Budget, the government allocated ₹2,000 crore for the IndiaAI mission – nearly a fifth of the scheme’s ₹10,370 crore presented last year.

Moreover, AIM lately reported that Indian companies and startups are increasingly using AI-enabled coding tools. Although companies were initially hesitant to adopt such tools, they are now leaning toward them due to their benefits.

Furthermore, a recent survey by GitHub revealed that 56% of Indian developers are using AI tools to help them boost their chances for employment owing to the skills they develop. Moreover, around 80% of them believe AI tools have improved code quality.

TVS Motor firm on Tuesday revealed plans to invest ₹2,000 crore in Karnataka over the next five years to establish a Global Capability Centre (GCC......

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The Indian Army has been rapidly embracing AI and autonomous systems to enhance national security while minimising human risks in combat. As modern wa......

iPhone users just got access to Gemini's Deep Research - how to try it

iPhone users just got access to Gemini's Deep Research - how to try it

iPhone clients can now tap into Google's Deep Research agent to research a topic on their behalf. Added to the Gemini website in December and to the Android app last month, the tool is now making its way to the iPhone version. Be aware, though, that Deep Research is available only to Gemini Advanced clients who pay $20 a month for the subscription.

Also: Google Gemini's lock screen modification is a game-changer for my phone.

Deep Research is Gemini's first agent, a new breed of AI bots that can perform tasks on their own. Submit your request or question, and the agent browses the web independently without you having to direct or manage it each step of the way.

When you submit a prompt with a specific question or request, Gemini delivers the standard type of AI-generated information. Want more? Tell it to turn to Deep Research. After scouring the web for more data, Gemini provides you with a full and comprehensive investigation, listing all the information it consulted.

Next, type or speak your query. In my case, I asked it for advice on health insurance plans for freelance contractors.

In response, Gemini hints at a plan for tackling your topic. You can edit that plan and tell the AI what changes you'd like to see. Gemini then presents you with an updated plan. If you like the plan, tap the "Start Research" button to send the AI on its way around the web.

Depending on the complexity of the topic and how many websites are researched, you'll likely have to wait at least a few minutes for the full study. At that point, tap the "Open" button for the study to read and review it.

The reports I received were well-organized and formatted with text, tables, and bullet points to make them easy to read. A list of all the researched websites appears at the bottom.

From the study, you can share it with someone else, open it in Google Docs, or select all the text. The conversation is saved to your chat history, so you can access the study at any time in the future.

You're able to kick off another request while one is already running, though Google limits how many you can run at the same time. You're also limited in the number of requests you can submit per day. But you'll be told if you're bumping up against the quota.

If you're on the fence about shelling out the $20 a month for a Gemini Advanced subscription, Google offers other perks beyond Deep Research. With this plan, you also score 2TB of storage, Google Photos editing aspects, 10% back in Google Store rewards, Google Meet premium video calling aspects, and Gemini for Workspace.

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‘We’d Like to Work With China,’ says OpenAI CEO Sam Altman

‘We’d Like to Work With China,’ says OpenAI CEO Sam Altman

OpenAI CEO Sam Altman revealed in an interview with British media outlet Sky News on Tuesday that the business would like to work with China. Altman made the comment when he was asked if he was worried about the country’s progress.

However, responding to a question about whether the US would let him do that, Altman expressed, “I know that for sure, no. Should we try as hard as we can? Absolutely, yes.”.

Altman’s statement follows the shockwave created by DeepSeek in the AI ecosystem, which has sparked concerns among several industry leaders who fear China’s rise.

in recent times, Dario Amodei, CEO of Anthropic, stated, “If we can close [export control loopholes] fast enough, we may be able to prevent China from getting millions of chips, increasing the likelihood of a unipolar world with the US ahead.”.

Similarly, in an interview with CNBC at the Davos World Economic Forum 2025, Microsoft CEO Satya Nadella expressed, “We should take the development of China very seriously.”.

Venture capitalist Vinod Khosla echoed the industry’s strongest fear. In a blog post, he earlier expressed, “We may have to worry about sentient AI destroying humanity, but the risk of an asteroid hitting the Earth or a pandemic also exists. But the risk of China destroying our system is significantly larger, in my opinion.”.

Altman’s take on China seems refreshing, to say the least.

In a podcast with The Times on Monday, while speaking about China’s DeepSeek, Altman stated, “They did some nice work. I think there’s also some nice pieces of product work like showing the chain of thought.” He went on to praise the research behind DeepSeek’s model, although he feels “it isn’t a big upgrade” to the ecosystem.

OpenAI reportedly has evidence that DeepSeek trained on its models and is investigating this with Microsoft. However, Altman not long ago revealed that the corporation does not plan to sue DeepSeek right now.

In the same interview with Sky News, Altman added, “I think we should probably open source somewhat more.”.

In a Reddit ‘ask-me-anything’ (AMA) session, he noted, “I personally think we have been on the wrong side of history here and need to figure out a different open-source strategy.”.

This comes at a time when industry leaders are rooting for the development of more open-source models, owing to DeepSeek’s recent success.

Meanwhile, Chamath Palihapitiya, a venture capitalist, stated in an interview, “I think in the war of open versus closed, open has won.”.

Palihapitiya believes OpenAI is now considering to open source what they’re doing in some way.

That mentioned, OpenAI has released multiple open-source models and tools in the past. The organization’s second iteration of the GPT model was also made available for open-source use.

IIT Madras and ISRO have developed and booted an indigenous aerospace-grade semiconductor chip based on RISC-V, an open-source Instruction Set Archite......

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Market Impact Analysis

Market Growth Trend

2018201920202021202220232024
23.1%27.8%29.2%32.4%34.2%35.2%35.6%
23.1%27.8%29.2%32.4%34.2%35.2%35.6% 2018201920202021202220232024

Quarterly Growth Rate

Q1 2024 Q2 2024 Q3 2024 Q4 2024
32.5% 34.8% 36.2% 35.6%
32.5% Q1 34.8% Q2 36.2% Q3 35.6% Q4

Market Segments and Growth Drivers

Segment Market Share Growth Rate
Machine Learning29%38.4%
Computer Vision18%35.7%
Natural Language Processing24%41.5%
Robotics15%22.3%
Other AI Technologies14%31.8%
Machine Learning29.0%Computer Vision18.0%Natural Language Processing24.0%Robotics15.0%Other AI Technologies14.0%

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity:

Innovation Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity AI/ML Blockchain VR/AR Cloud Mobile

Competitive Landscape Analysis

Company Market Share
Google AI18.3%
Microsoft AI15.7%
IBM Watson11.2%
Amazon AI9.8%
OpenAI8.4%

Future Outlook and Predictions

The Indian Companies Bullish landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:

Year-by-Year Technology Evolution

Based on current trajectory and expert analyses, we can project the following development timeline:

2024Early adopters begin implementing specialized solutions with measurable results
2025Industry standards emerging to facilitate broader adoption and integration
2026Mainstream adoption begins as technical barriers are addressed
2027Integration with adjacent technologies creates new capabilities
2028Business models transform as capabilities mature
2029Technology becomes embedded in core infrastructure and processes
2030New paradigms emerge as the technology reaches full maturity

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:

Time / Development Stage Adoption / Maturity Innovation Early Adoption Growth Maturity Decline/Legacy Emerging Tech Current Focus Established Tech Mature Solutions (Interactive diagram available in full report)

Innovation Trigger

  • Generative AI for specialized domains
  • Blockchain for supply chain verification

Peak of Inflated Expectations

  • Digital twins for business processes
  • Quantum-resistant cryptography

Trough of Disillusionment

  • Consumer AR/VR applications
  • General-purpose blockchain

Slope of Enlightenment

  • AI-driven analytics
  • Edge computing

Plateau of Productivity

  • Cloud infrastructure
  • Mobile applications

Technology Evolution Timeline

1-2 Years
  • Improved generative models
  • specialized AI applications
3-5 Years
  • AI-human collaboration systems
  • multimodal AI platforms
5+ Years
  • General AI capabilities
  • AI-driven scientific breakthroughs

Expert Perspectives

Leading experts in the ai tech sector provide diverse perspectives on how the landscape will evolve over the coming years:

"The next frontier is AI systems that can reason across modalities and domains with minimal human guidance."

— AI Researcher

"Organizations that develop effective AI governance frameworks will gain competitive advantage."

— Industry Analyst

"The AI talent gap remains a critical barrier to implementation for most enterprises."

— Chief AI Officer

Areas of Expert Consensus

  • Acceleration of Innovation: The pace of technological evolution will continue to increase
  • Practical Integration: Focus will shift from proof-of-concept to operational deployment
  • Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
  • Regulatory Influence: Regulatory frameworks will increasingly shape technology development

Short-Term Outlook (1-2 Years)

In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing ai tech challenges:

  • Improved generative models
  • specialized AI applications
  • enhanced AI ethics frameworks

These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.

Mid-Term Outlook (3-5 Years)

As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:

  • AI-human collaboration systems
  • multimodal AI platforms
  • democratized AI development

This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.

Long-Term Outlook (5+ Years)

Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:

  • General AI capabilities
  • AI-driven scientific breakthroughs
  • new computing paradigms

These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.

Key Risk Factors and Uncertainties

Several critical factors could significantly impact the trajectory of ai tech evolution:

Ethical concerns about AI decision-making
Data privacy regulations
Algorithm bias

Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.

Alternative Future Scenarios

The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:

Optimistic Scenario

Responsible AI driving innovation while minimizing societal disruption

Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.

Probability: 25-30%

Base Case Scenario

Incremental adoption with mixed societal impacts and ongoing ethical challenges

Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.

Probability: 50-60%

Conservative Scenario

Technical and ethical barriers creating significant implementation challenges

Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.

Probability: 15-20%

Scenario Comparison Matrix

FactorOptimisticBase CaseConservative
Implementation TimelineAcceleratedSteadyDelayed
Market AdoptionWidespreadSelectiveLimited
Technology EvolutionRapidProgressiveIncremental
Regulatory EnvironmentSupportiveBalancedRestrictive
Business ImpactTransformativeSignificantModest

Transformational Impact

Redefinition of knowledge work, automation of creative processes. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.

The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.

Implementation Challenges

Ethical concerns, computing resource limitations, talent shortages. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.

Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.

Key Innovations to Watch

Multimodal learning, resource-efficient AI, transparent decision systems. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.

Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.

Technical Glossary

Key technical terms and definitions to help understand the technologies discussed in this article.

Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.

Filter by difficulty:

large language model intermediate

algorithm

platform intermediate

interface Platforms provide standardized environments that reduce development complexity and enable ecosystem growth through shared functionality and integration capabilities.

API beginner

platform APIs serve as the connective tissue in modern software architectures, enabling different applications and services to communicate and share data according to defined protocols and data formats.
API concept visualizationHow APIs enable communication between different software systems
Example: Cloud service providers like AWS, Google Cloud, and Azure offer extensive APIs that allow organizations to programmatically provision and manage infrastructure and services.