Businesses today face an overwhelming “data tsunami” — a surge of data that, while valuable, often hampers application performance and strains architectural scalability. The more data an organization manages, the more challenging these issues become. With AI workloads adding to data management complexities, enterprises are looking for ways to achieve scalability, maintain performance, and meet evolving data demands.

CIO Dimension spoke with Bhanu Jamwal, Head of Presales & Solution Engineering, APAC, TiDB, to explore how a modern and innovative approach to databases is helping businesses overcome these challenges and innovate. TiDB – an open source distributed SQL database developed by PingCAP – tries to provide some answers. 

How is PingCAP’s TiDB positioning itself in the competitive database market, particularly considering the rapid growth of digital native businesses in India?

We’ve witnessed a remarkable surge in digital native businesses across India, spanning e-commerce, logistics, fintech, gaming, SaaS, and more recently, the emerging healthcare and Gen AI sectors. This explosive growth, however, comes at a cost – a massive influx of data.

Their increasing reliance on data creates a greater demand for scalable and reliable data solutions. Traditional databases often struggle to scale to meet this kind of growth and volume. Imagine a scenario where an e-commerce platform, during a peak sales event experiencing a huge surge in transactions. Traditional databases, such as MySQL or PostgreSQL, may encounter performance bottlenecks under such pressure.

Businesses are therefore compelled to either implement workarounds or adopt modern database solutions that can address these challenges. And these challenges now go beyond just scale. High availability is paramount; downtime is simply not an option today. Real-time analytics is another critical factor businesses. For instance, a bank needs to be able to detect fraudulent transactions in real-time to safeguard customer funds. So, it needs, scalability, availability and analytics- all at the same time. AI introduces further complexities and challenges to this mix. 

Recognizing these evolving needs, TiDB was born in 2015. We strive to address these challenges with our distributed architecture, which allows businesses to scale as their data grows. Distributed SQL databases have in fact emerged as an effective answer to modern data challenges. This approach has been gaining traction, as evidenced by Amazon’s recent entry into the distributed SQL market, acknowledging the growing demand for such solutions. 

How do you view the SQL vs. NoSQL debate, and how does TiDB position itself in this context?

The SQL vs. NoSQL debate has been ongoing for some time with both playing pivotal roles in enterprise environments. While NoSQL databases offer flexibility for specific use cases, they often require significant development effort to maintain data structures. SQL, on the other hand, remains the de facto standard for data access, with a vast pool of skilled developers. 

It’s interesting how many NoSQL databases, which originally distanced themselves from SQL, are now adding SQL layers to their platforms. It shows that SQL remains a simple and effective way to access data. 

TiDB’s aim is to bring best of both by offering a distributed SQL solution. Our Hybrid Transactional/Analytical Processing (HTAP) capabilities are designed to bridge the gap between SQL and NoSQL databases and handle both transactional and analytical workloads. 

How is AI and ML, particularly the rise of LLMs, changing the game for distributed databases, and how is TiDB capitalizing on these trends?

The rise of vector database is a trend worth mentioning in this context. Vector is becoming a powerful engine for today’s AI workloads. Though it has been around for a while, the adoption has rapidly scaled in recent years. These databases are becoming increasingly crucial for storing and processing the data generated by AI/ML models. 

But, this also makes the environment quite complex for enterprises. They often manage multiple databases for different workloads—a transactional database, a separate one for analytics, and yet another for vector storage. Managing databases is a complex process. 

At TiDB, we see an opportunity to simplify this process by offering a unified solution. Our vision is to provide a single database that handles all these workloads, eliminating the need for multiple systems. TiDB supports vector as a form of storage with TiDB serverless, enabling organizations to store and process both traditional data and vector data within a unified platform. We believe the integration of vector search capabilities into a traditional database will be a game-changer for businesses looking to leverage the power of AI and ML. 

Can you share some successful case studies of TiDB implementations in India and globally?

Absolutely! We have a number of success stories across various industries. In India, a leading e-commerce giant was struggling to manage the increasing complexity of their database infrastructure as they scaled, relying on a multitude of single-node databases. By migrating to TiDB, they consolidated their infrastructure, significantly improved performance, and gained greater operational efficiency. 

Delhivery, a leading logistics company that delivers a million packages a day, migrated to TiDB to power their real-time analytics and data marts use case, enabling them to handle thousands of requests per second with less than 100ms latency. 

Pinterest is another flagship customer that leveraged TiDB to modernize their data architecture. Globally, we’ve seen tremendous success in the fintech sector. A major Japanese fintech company, for example, experienced a 10x increase in throughput and a 30% reduction in latency after adopting TiDB for their high-volume wallet application. 

We’re also seeing significant growth in the SaaS market, where TiDB helps companies manage the complexities of multi-tenant environments and scale their databases to support growing user bases.

What are the key market opportunities for TiDB in India?

India is a dynamic and rapidly growing market with a thriving startup ecosystem. We see immense potential here. The sheer volume of data generated by India’s digital-native businesses and startups, coupled with their ambitious growth plans, creates a strong demand for distributed database solutions. India’s thriving Web3 community, its vast base of skilled developers are all opportunities that TiDB will be actively tapping into. 

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As we step into 2025, Securonix offers key predictions on the evolving cybersecurity landscape. Reflecting on 2024, we saw a surge in cloud intrusions, malware-free attacks, and escalating breach costs, underscoring the urgent need for advanced defenses. With innovations like AI-powered insider threat detection and behavioral analytics leading the charge, the future holds transformative potential.

In 2025, Securonix foresees AI revolutionizing SOCs, quantum-safe algorithms addressing encryption risks, and greater collaboration through shared threat intelligence. MSSPs and advanced data management solutions like Cyber Data Fabric will play pivotal roles in shaping efficient, proactive cybersecurity strategies for the challenges ahead.

Here’s a glimpse into 2024 and crystal ball view into 2025 from Securonix. 

2024: Year in Review

●      Rise in Threat Activity: Threat activity surged with cloud intrusions rising by 75% as organizations increasingly adopted cloud solutions

●      Shift in Attack Strategies: Malware-free attacks grew, leveraging legitimate tools within environments instead of external malware

●      Escalating Costs: The mean cost of a data breach had reached $4.88 million, thereby pointing to the severe need for advanced cybersecurity measures

●      AI Integration: Securonix unveiled Eon, which integrated such innovation as insider threat detection through psycholinguistics, a clear example of how the industry was now turning to AI

●      Insider Threats: Studies indicated that 60% of breaches occur through insider threats, making advanced behavioral analytics crucial

2025: Prepping for the Future

●      AI in Cybersecurity: AI will make the SOCs more efficient, reducing the workload of analysts and making responses more efficient

●      Quantum Computing and Encryption: The risks associated with emerging Quantum technologies have threatened encryption protocols, leading to the need for quantum-safe algorithms

●      Insider Threats on Rise: The push for return-to-office poses insider risks with employees and hence the need for behavioral analytics is key

●      Collaboration Among Organizations: Shared threat intelligence will increase, allowing organizations to identify and fight threats together

●      Data Pipeline Management: Solutions for effective data routing, such as Securonix’s Cyber Data Fabric, will be critical in managing SIEM costs and optimizing analytics

●      Expansion of MSSPs: MSSPs will become more prominent, supporting hybrid SOC models and handling advanced threat responses

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Business leaders have high hopes that artificial intelligence (AI) investments can drive market-changing innovations to transform everything from customer satisfaction to product innovation. However, a poor data foundation is holding 78% of organisations back from achieving these goals.

A new report from MIT Technology Review Insights, in partnership with Snowflake, the AI Data Cloud company, titled ‘Data Strategies for AI Leaders’ found that while businesses have big ambitions for generative AI — with 72% looking to increase efficiency or productivity, 55% betting on increased market competitiveness, and 47% aiming to see more innovation in products and services — the foundational data strategy needs to be improved to maximise AI’s potential.

Businesses need strong data foundations, powered by modern cloud data platforms, to enable them to harness their own stores of data, and also vast volumes of previously inaccessible data, largely from unstructured data such as videos and images. According to the report, just 22% of business leaders say they are ‘very ready’ to engage with AI, while 53% are ‘somewhat ready’. Higher readiness correlates with fewer challenges related to accessing scalable computing power, data silos and integration issues, and data governance. Despite many business leaders’ confidence in the results AI can deliver, they are realising that data is key to how quickly and effectively they can unlock AI’s value.

Another challenge facing organisations is deploying AI at scale. 95% of those surveyed reported facing hurdles when implementing AI. 59% of respondents cited data governance, security, or privacy as their most prevalent challenge, followed by data quality and timeliness (53%), and costs of resources or investment (48%). Spending and resourcing decisions, including those needed to improve data foundations, are a challenge when it comes to any technology investment. But the cost of generative AI itself is decreasing, with enterprises having begun to build smaller large language models (LLMs) that remain equally capable, and less expensive.

“Many of today’s organisations have big ambitions for generative AI: they are looking to reshape how they operate and what they sell,” says Baris Gultekin, Head of AI, Snowflake. “Our joint research shows that as organisations feel increasing urgency to deploy AI applications, they are realising that their data can help them deliver insights from previously untapped sources of information. A strong data foundation is at the core of generative AI capabilities, and business leaders need to move quickly to deal with concerns such as data security and cost, and establish the foundation they need to deliver on the promise of AI.”

Generative AI’s benefits are becoming visible to those companies farther along their data journey, because they invested heavily in data foundations and are now being rewarded by bringing AI onto that data. For any business looking to capitalise on AI, they must first establish a robust data foundation, which covers a broad collection of processes and assets involved in the gathering, aggregation, storage, and accessibility of organisational data. Investment in data foundations across an organisation will enable much more powerful generative AI users, while also reducing governance and security concerns.

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For CIOs and CTOs, AI can automate routine tasks like network monitoring, system maintenance, and cybersecurity, reducing the need for hands-on management. This gives them more time to focus on innovation and developing long-term technology strategies. AI also helps them make data-driven decisions by providing insights from vast amounts of data, which allows companies to anticipate customer needs, improve operations, and create new products or services.

However, AI also presents new challenges. CIOs and CTOs will need to navigate ethical concerns around AI, such as data privacy and the impact of automation on jobs. They’ll also need to continuously update their skills to keep up with rapidly advancing AI technologies.

Moreover, AI is driving the need for strong collaboration between CIOs/CTOs and other departments like human resources, marketing, and finance. For instance, AI systems that monitor employee performance or improve customer experience require cross-functional alignment. This means CIOs and CTOs must become more integrated with the business side, ensuring that AI initiatives are aligned with overall company goals.

As companies continue to adopt AI-driven solutions, the demand for CIOs and CTOs who understand both technology and business strategy will grow. Embracing this shift will help them not only lead but also innovate in today’s competitive landscape. Those who stay ahead will be the driving force behind their organization’s success.

References:

• Forbes: How AI is Reshaping the Role of the CIO
• Gartner: Gartner Says Three-Fourths of CIO Job Description Will Be Rewritten by 2024

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MongoDB announced a partnership with All India Council for Technical Education (AICTE), Ministry of Education, Government of India to give more than 150,000 Indian students access to virtual internships and to gain the skills required to use MongoDB Atlas—the leading multi-cloud developer data platform. 

This partnership with AICTE, the Indian government’s authority for the management of technical education, is part of the company’s ‘MongoDB for Academia’ initiative and will be supported by SmartBridge’s SmartInternz learning platform. Each internship will include 60 hours of experiential learning, hands-on bootcamps, courses, and project work, as well as simulated corporate environments where students can apply their learned skills, collaborate with peers, and receive mentorship. 

Launched in September 2023, the MongoDB for Academia in India program provides student training, curriculum resources for educators, credits to use MongoDB technology at no cost, and certifications to help individuals start careers in the technology industry. The skills and training provided through the program are particularly important, as many Indian organizations struggle to find developers who have the skills to build modern applications and take advantage of emerging technologies like generative AI, the company maintained. 

According to a report from NASSCOM, India’s technology sector will demand more than one million engineers with advanced skills in artificial intelligence and other capabilities over the next three years. Overall, the industry body expects there will be a need for around six million digital roles by 2028—and the available talent pool is forecast to be 4.7 million workers. This gap underscores the need for increased collaboration between industry and academia to upskill students and educators in India to meet the demands of the country’s large and growing economy. 

“In India, we have a massive opportunity with the current wave of AI and modern technologies that will transform our lives and economy in the coming years. But to take advantage of that opportunity, it is vital our developers have the right skills. We’re excited to partner with MongoDB to help make that possible,” said Dr. Buddha Chandrasekhar CEO, Anuvadini AI, Ministry of Education and Chief Coordinating Officer, AICTE, Ministry of Education, Government of India.

“We’ve seen great appetite and interest on our platform for modern database technologies like MongoDB. We want to equip students with knowledge of in-demand technologies so they have skills they need to become the job-ready candidates India’s organizations are looking for,” said Amarender Katkam, Founder and CEO at SmartBridge and SmartInternz. 

“India loves developers and so does MongoDB. I’m so proud of the work our MongoDB for Academia team is doing to empower Indian developers and to support the next generation of tech talent in this country,” said Sachin Chawla, Area Vice President, India at MongoDB.

As part of the program’s expansion, MongoDB also announced a new partnership with GeeksforGeeks, a platform for computer science resources in India. The collaboration will make the MongoDB Developer Learning Path available to all of GeeksforGeeks’ 25 million registered users.

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Securonix, Inc. announced that Kash Shaikh has been appointed President and Chief Executive Officer and member of its Board of Directors, effective immediately.

Kash succeeds Nayaki Nayyar who has been serving as the CEO of the security vendor since December 2022. Nayaki has decided to step down and focus the next phase of her career on public Board service, the company said in a press release. 

Kash is a seasoned enterprise technology Executive with Fortune 50 experience and has a record of driving profitable growth across Software, SaaS, and AI Infrastructure markets. 

He has over 30 years of experience of fostering business transformation and delivering innovative technology solutions for global enterprise organizations. He most recently served as President and CEO of Virtana, a leading hybrid-cloud infrastructure observability solutions provider.

Prior to Virtana, Shaikh served as Global Vice President and General Manager for Dell’s Enterprise Solutions Unit. Shaikh has also held leadership and executive positions at Ruckus Wireless, Hewlett Packard, Cisco, and Nortel Networks.

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Indian CEOs place great importance on AI governance, with a significant 71% believing that trusted AI is impossible without effective AI governance in organizations. A global study of 3,000 CEOs conducted by IBM Institute for Business Value, in cooperation with Oxford Economics, reveals a number of interesting aspects about workforce, culture and governance challenges faced by Indian CEOs while navigating AI journeys. 

According to the study, 75% Indian CEO respondents say governance for generative AI must be established as solutions are designed, rather than after they are deployed. At the same time, the study also noted a contrast in actual adoption of AI governance policies with only 42% Indian CEO respondents saying they have good generative AI governance in place today.

The survey also highlights other key challenges around workforce. 75% of Indian CEO respondents say that inspiring their team with a common vision produces better outcomes than providing precise standards and targets. Yet 31% acknowledge that their employees don’t fully understand how strategic decisions impact them.

Sandip Patel, Managing Director, IBM India & South Asia said, “As Indian CEOs navigate AI-led transformations within their organizations, they recognize the need for AI guardrails so that they derive real business value responsibly for growth and competitive success. However, our study reveals a gap between their intention and actual implementation. This scenario highlights the complexity of implementing AI governance, hence making a strong case for partnering with trusted experts to develop and execute effective practices and policies.”

Other key study findings include:

People and skills are at the heart of successful generative AI adoption

• 71% of Indian CEOs surveyed say that succeeding with AI will depend more on people’s adoption than the technology itself
• 49% of Indian CEO respondents says they are hiring for Gen AI roles that didn’t exist last year
• CEOs surveyed from India say 34% of their workforce will require retraining and reskilling over the next three years – up from just 6% globally in 2021

Indian CEOs recognize it takes a cultural shift to successfully scale AI, but face organizational collaboration and adoption challenges.

• 70% of Indian CEOs surveyed say their organization’s success is directly tied to the quality of collaboration between finance and technology, yet nearly half (48%) say competition among their C-Suite executives sometimes impedes collaboration.
• Nearly half (48%) of those surveyed from India acknowledge that cultural change is more important to becoming a data-driven organization than overcoming technical challenges.
• 58% of Indian CEO respondents say they are pushing their organization to adopt generative AI more quickly than some people are comfortable with

Customer experience and product & service innovation are top priorities, regulatory constraints might be hindering long-term progress

• Indian CEOs surveyed ranked customer experience and product & service innovation as their highest priorities for the next three years
• 59% of respondents say they are willing to sacrifice operational efficiency for greater innovation.
• However, nearly half (48%) of Indian CEOs surveyed point to regulatory constraints as their top barrier to innovation.
• Today, only 32% of the Indian CEO respondents are primarily funding their generative AI investments with net new IT spend, with the remaining 68% reducing other technology spend.

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As Wimbledon fever grips the world, a Generative AI-powered tool will help fans across the globe to stay up to date with personalized player stories. The All England Lawn Tennis Club, also known as the All England Club where the Wimbledon championship is held, has expanded its three-decade long partnership with IBM to further leverage GenAI. 

The tech giant’s partnership with the All-England Lawn Tennis Club (AELTC) has driven digital transformation at Wimbledon for more than 30 years. This year, we will witness a new feature for the Wimbledon digital experience that will leverage match data with generative AI from IBM’s AI and data platform, watsonx, to keep fans updated on the world’s leading players as they advance through The Championships.

The new ‘Catch Me Up’ feature displays pre and post-match player cards with AI-generated player stories and analysis via wimbledon.com and the Wimbledon 2024 App. Player cards will be personalised based on user preferences and data such as their location and myWimbledon profile, starting with their favourite players. Pre-match content will include analysis of recent performance and likelihood to win predictions, and post-match it will include key statistics and highlights. The feature will also create longer-form daily summaries of play.

‘Catch Me Up’ was built using IBM’s Granite large language model (LLM) to provide AI-generated text using the capabilities of the watsonx platform. The model has been trained on the Wimbledon editorial style and will be monitored by the All England Club. The new feature is designed to help Wimbledon scale its content to both new and existing tennis fans globally, as well as provide fans access to timelier, curated coverage across ladies’ and gentlemen’s singles matches which are often happening simultaneously.

This year, Wimbledon will also use generative AI to provide coverage of a broader range of matches than was previously available, including wheelchair events, to offer more to Wimbledon’s diverse international audience. This will form part of a redesigned digital match centre, known as IBM Slamtracker, available on the Wimbledon App and wimbledon.com. Using generative AI built from watsonx, IBM Slamtracker has been enhanced to  provide bullet point-based match previews and post-match reviews for ladies’ and gentlemen’s singles matches.

“We are committed to offering fans the highest quality Wimbledon experience, whether it’s in person or digitally. Generative AI allows us to scale our ability to provide different types of content for fans wherever they are in the world in a way that’s personalised for them. This year’s new Catch Me Up feature will make it easier for fans to follow the key storylines as they emerge throughout The Championships.”

Chris Clements, Digital Products Lead at the All England Club, 

“The new Catch Me Up feature is an exciting example of how we can use the power of generative AI to deliver compelling, insight-driven storytelling at scale. For 35 years, IBM and Wimbledon have been co-creating solutions that make fans feel more connected to all the on-court action, and our new research confirms they are beginning to understand the positive impact technologies such as generative AI can have on their digital experiences…”

Jonathan Adashek, Senior Vice President of Marketing and Communications for IBM

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Cisco Investments, the global corporate venture investment arm of Cisco launched a $1B AI investment fund to bolster the startup ecosystem and expand the development of secure and reliable AI solutions. As part of the new AI fund, Cisco is making strategic investments in Cohere, Mistral AI and Scale AI among others. Cisco has already committed nearly $200M of the $1B investment fund to date.

Over the past several years, Cisco has made over 20 AI-focused acquisitions and investments, furthering GenAI and Machine Learning capabilities and integration of AI across the Cisco portfolio. In addition to these investments, Cisco will also be working with AI companies on product collaborations that allow Cisco to co-innovate, while also being an agnostic provider and platform player in AI, offering options and coverage for Cisco’s global customer base.

The committed investments in the new AI fund include:

• Cohere: Headquartered in Toronto and San Francisco, Cohere provides security-focused frontier large language models (LLMs) and industry-leading Retrieval-Augmented Generation (RAG) capabilities tailored to meet the needs of enterprises.
• Mistral AI: Mistral AI is a global company headquartered in Paris specializing in generative artificial intelligence. The company develops new models of generative artificial intelligence for businesses, combining scientific excellence, an open approach and a responsible vision of technology.
• Scale AI: Based in the U.S., Scale AI provides a data-centric, end-to-end platform providing training and validation for AI applications. Cisco recently participated in Scale AI’s Series F funding as the round’s largest strategic investor.

“The establishment of our $1 billion AI investment fund is a testament to our commitment to the transformative power of artificial intelligence and its potential to redefine industries globally,” said Derek Idemoto, SVP, Corporate Development and Cisco Investments. “This fund represents our unwavering commitment to AI and innovation, and to the entrepreneurs and visionaries who are defining the next wave of technology.”

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Deloitte has released its “2024 Financial Services Industry Predictions,” which outlines some of the most significant emerging trends across the financial services industry over the next three to five years. Among the most significant trends, the report highlights the impact AI could have on transforming retail investing, enabling deepfakes and fraud in banking and driving new insurance offerings. Climate change is also predicted to continue to increase insurance costs for commercial real estate property owners and impact profitability of insurers.

“The seismic shifts we will see in financial services as a result of emerging technology and innovation will likely be transformative and provide new opportunities for growth,” said Jim Eckenrode, managing director, Deloitte Center for Financial Services, Deloitte Services LP. “At the same time, financial services organizations will face new risks and resiliency challenges, including market volatility, impact from climate change, talent gaps and new regulations, and organizations should plan now for what’s on the horizon.”

Highlights of Deloitte’s 2024 Financial Services Industry Predictions include:

Retail investors may soon rely on Generative AI for financial investment advice: Deloitte predicts GenAI-enabled applications will likely become the leader in advice mind-space for retail investors, growing from its current nascent stage to 78% usage in 2028 and could become the leading source of retail investment advice by 2027ⁱ. 

Generative AI expected to magnify the risk of deepfakes and other fraud in banking: Hyper-realistic fake content has never been easier to create—or harder to catch. As threats grow, banks should invest in AI and other technologies to help detect fraud and prevent losses. Deloitte predicts GenAI could enable fraud losses to reach $40 billion in the US by 2027, up from $12.3 billion in 2023ⁱⁱ.

Providing insurance coverage for AI may be a blue ocean opportunity: Regulatory guidance, large losses and market demand may drive the need for AI insurance, and some insurers and insurtech startups are already developing products in this space. While the opportunity is massive, insurers will likely also face difficulties in assessing and pricing the complex and evolving risks of AI. Deloitte predicts that by 2032, insurers can potentially write ~$4.7 billion in annual global AI insurance premiums, at a compounded annual growth rate of around 80%.

Climate change to increase commercial real estate insurance costs: The links between climate change, extreme weather and insurance costs will likely remain for the foreseeable future. Deloitte predicts that the average monthly cost of insurance for a commercial building in the US could increase from $2,726 per month in 2023 to $4,890 per month in 2030, at an 8.7% compound annual growth rateⁱⁱⁱ. For states with the greatest extreme weather risk, current monthly costs could more than double.

Climate change and homeowners’ insurance: Similarly, climate change and severe weather events are also dramatically affecting the profitability and sustainability of the US homeowners’ insurance sector. Deloitte predicts that if insurers, in partnership with government agencies and policyholders, invest $3.35 billion in residential dwelling resiliency measures, the two thirds of US homes that are not currently built to code could be made resistant enough to reduce many weather-related claims losses. These actions could, in fact, save insurers as much as $37 billion by 2030^iv.

Additional trends included in the report that are expected to shape the financial services industry:

In-app payments expected to take social commerce to the next level: Social media platforms are transforming into the new “storefronts” for consumers, who can discover and buy products within the apps. Deloitte predicts that in-app payments on social media sites could grow at a compound annual growth rate of about 30% from $19.1 billion in 2024 to $94.5 billion in 2030^v.

AI can accelerate the portfolio valuation process: AI can help private investment firms increase the frequency and transparency of their portfolio valuations and attract more retail investors. There will be benefits and challenges of using AI for portfolio valuations, such as mitigating the denominator effect, satisfying limited partners’ information needs and complying with regulatory requirements. Deloitte predicts as many as 25% of private equity firms will be using AI to augment their portfolio valuations^vii.

“As financial services firms face an ever-changing landscape, they should think about what’s on the horizon,” said Monica O’Reilly, Vice Chair, US Financial Services Industry Leader, Deloitte & Touche LLP. “Market pressures and emerging risks as well as new growth opportunities will shape business strategies, and financial services firms should prepare for that now.”

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