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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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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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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UST, a digital transformation solutions company, has launched a massive new initiative to train over 25,000 of its employees globally in Generative AI (GenAI) and provide opportunities for career advancement. This ambitious program underscores UST’s ongoing efforts to comprehensive workforce training and upskilling, keeping its talented personnel future-ready, the company stated. 

The program comes just months after the unveiling of UST AlphaAI, which consolidates the company’s AI offerings to enhance business agility, streamline operations, and accelerate digital transformation journeys.

UST will offer a range of GenAI training programs that are specifically tailored to its employees and their different roles and responsibilities, improving efficiency while helping each employee reach their own unique potential. 

The training program will build upon insights gained through UST’s collaboration and partnership with AI researchers from renowned academic institutions such as the MIT Computer Science & Artificial Intelligence Laboratory and the Stanford Artificial Intelligence Laboratory. This legacy of close collaboration with leading researchers will help UST expand on its culture of continuous learning by bringing the latest academic breakthroughs to its workforce, according to a press release issued by the company. 

“Our comprehensive GenAI training initiative will set a new industry standard and bring over 25,000 employees up to speed on everything from foundational GenAI concepts to cutting-edge applications. Adaptable and customizable for each participant, the flexible training program provides hands-on experience with industry-leading tools and platforms like GitHub Copilot, setting our employees up for future success by ensuring that they can apply GenAI capabilities across diverse domains, said Sunil Balakrishnan, Chief Values Officer and Global Head – Development Canter Operations, UST.

“At UST, we recognize that the key to staying competitive in today’s fast-paced digital landscape lies in the continuous upskilling of our workforce. As GenAI continues to revolutionize industries and transform business operations, we remain dedicated to equipping our employees with the tools and knowledge they need to leverage these cutting-edge technologies effectively,” said Dr. Adnan Masood, Chief AI Architect, UST.

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The Generative AI (GenAI) wave is upon us. Every enterprise is buzzing about its potential, and investments are skyrocketing. But amidst the excitement, a crucial question remains: What truly separates successful GenAI projects from the rest?

In a recent visit to India, Jihad Dannawi, Regional VP – APAC, DataStax (a leading real-time vector database company) sheds light on the hidden complexities of AI projects. This exclusive interview with CIO Dimension delves into:

• The power of the right database in unlocking the true potential of Large Language Models (LLMs)
• Why developers are the backbone of GenAI and how to empower them
• India’s unique advantage in leading the GenAI revolution

Edited excerpts: 

DataStax positions Astra DB as the ‘go-to’ database for GenAI applications. Can you explain why Astra DB stands out as the best choice for GenAI applications compared to your competition?

For starters, we are a 14-year-old company that has built the most widely used enterprise-grade database. It has been delivering high scale, high performance, and high availability — even before Generative AI came in. 

We are at a stage where a lot of organizations are scaling GenAI from PoC to production. At PoC level, organizations are not looking at scale or performance. But when they move to production, they suddenly start to have performance issues. They need to be able to pull in massive amounts of data to increase the relevancy and accuracy of the models, which means that the database must be bigger.

But volume often comes in the way of performance at the production stage. When organizations move beyond entry level scenarios to more mature use cases, they need to have a database that can handle their speed, scale, and performance requirements      – all at a reasonable TCO. A lot of databases in the market struggle to balance these aspects. 

An industry benchmark clearly demonstrates that DataStax’s Astra DB Serverless (the cloud-native database service built on Apache Cassandra) significantly outperforms the competition in throughput, latency, relevance, and TCO.  

Another key offering from DataStax is RAGStack, which claims to reduce the complexity associated with Gen AI for developers? Could you elaborate? 

When it comes to generative AI, one of the key issues that the developer community faces – especially when they start building the big stuff for production – is that they don’t know where to start. Because there are so many components and tools available in the market, it’s hard to decide what to use –  especially when dealing with vector databases.   

That’s why DataStax built a layer for the developers called RAGStack. This helps them build production-grade retrieval augmented generation (RAG) Gen AI applications in a simpler and faster way – without the developers having to learn everything from      scratch. It’s fully open source, connected and improves developer productivity significantly. It drastically simplifies the process of implementing RAG – the process of providing context from outside data sources to deliver more accurate LLM query responses. 

RAGStack is part of our vision is to enable and empower developers to build GenAI applications in production more efficiently. We are helping developers and companies to quickly innovate.  Developers do not come with AI skills; they don’t know how to build LLMs. We firmly believe that the GenAI journey of an organization starts from the developer, and not the AI team. With RAGstack, they can start right away, without waiting to acquire new skills. 

Another major concern that organizations must deal with is the AI hallucination. How is DataStax working to ensure fewer hallucinations? 

Hallucination, or in other words the “context” for an LLM, is the tricky bit. Now technology allows you to launch GenAI very quickly, but GenAI is not always accurate. This is why retrieval augmented generation (RAG) is so important for enterprises building GenAI applications. They must be able to augment an LLM with relevant, up-to-date data so it can provide relevant, factual responses.

More data means better context. And this will also bring in the big competitive differentiator into the models and the eventual outcomes for businesses. This further emphasizes the point that many databases in the market that claim to be vector do not have the capacity to perform high volume data. 

Can you share some examples of how Astra DB has helped customers achieve significant business outcomes?

Through Astra, we have started to discover a lot of customers with smaller needs, who can move very quickly through the GenAI journey. When customers begin to deploy impactful GenAI in their business processes, we believe that we stand to gain.  

A great case in point is Skypoint, the Portland-based Gen AI healthcare company. They leverage Astra DB’s vector search to enhance their services, offering users real-time, contextual, and personalized AI agent solutions. 

Another key customer for us is India’s leading edtech player, Physics Wallah. This unicorn’s app has over 15 million downloads as of January 2024. Its personalized AI bot is built on Astra DB and assists students with their academic and support queries in a personalized manner. The database’s stability helped the company handle 50x traffic increase with zero downtime during a live demo with 1 million students.  

A lot of organizations are still in the experimentation stage. Our study shows that only 4% of GenAI projects have moved to production, so we are in the absolute beginning of the wave, a lot of the     projects in PoC will move in     to production this year.      

India’s GenAI market is predicted to reach a massive $17B by 2030 and India is reportedly ahead of the US in AI adoption by businesses. What will be the catalysts for this growth and what are DataStax’s plans to capitalize on this opportunity?

AI will impact the top line and bottom line of every business out there. India has a strong community of developers and GenAI starts with developers. So, India has the skills and the mass to innovate and drive more use cases. They      also have the right mindset – the ecosystem here loves to build and that’s a very positive mindset to have when it comes to AI. Because AI is not something you buy and turn on, it’s something you build. And with the right mindset, India will be faster to innovate. The GenAI wave is poised to trigger a paradigm shift, comparable to the impact of mobile and web technologies. India has the skills, capacity and the mindset to really benefit.  

From a DataStax point of view, India is a big market and we are definitely investing here. We are expanding our team to meet to the growing needs.  

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When Mitali Biswas left her highly fulfilling role at IBM to become the CIO of a leading hospital in Kolkata, she was led solely by her conviction. Four years later, after successfully navigating the COVID-19 crisis which came along rather unexpectedly, she has embraced the role of a CIO with all its virtuosity. 

The secret sauce is her inside-out approach to digital transformation with a firm focus on impactful outcomes. She is the sort of a technology leader who has seen the best of transformation programs globally and yet champions a more grounded approach while crafting a technology roadmap at CK Birla Hospitals. 

In this exclusive video interaction, Mitali takes us through her fascinating journey as a healthcare CIO and how the sector is set to transform itself with the help of AI, IoT, wearables and other technologies. 

The CK Birla group of Hospitals comprises esteemed institutions such as the Calcutta Medical Research Institute (CMRI), a premier multispecialty hospital located in Kolkata, alongside the renowned BM Birla Heart Research Centre in Kolkata and the Rukmani Birla Hospital in Jaipur. With a rich legacy spanning over 50 years, these hospitals have collectively provided care to more than 1.8 million patients.

Mitali believes that AI has the ability to revolutionize the healthcare sector and save more lives. 

“AI has potential to significantly transform the clinical decisions support systems, by helping doctors diagnose faster and more accurately using data. Radiology imaging is emerging as a strong use case today. Imagine AI being used to accelerate the diagnosis process of brain strokes using MRI images – we will be able to save a lot more lives this way,” she says. 

She discussed some key roadblocks to AI adoption in healthcare from an Indian context. “In healthcare, we are dealing with human lives and there must be the trust and evidence that the AI systems are 100 percent right. That’s the reason why acceptance and change management remain the biggest challenges.” 

Mitali also highlights some key challenges in implementing AI in healthcare including the prevalence of manual processes, and the data management & data sharing issues that CIOs face. “It’s important to get the entire ecosystem in the healthcare sector to work together. Government plays a key role here. I think we are heading in the right direction with the help of Ayushman Bharat Digital Mission. Enforcement is the need of the hour,” she underscores.  

Watch the full video to learn more about the emerging use cases of IoT and wearables in healthcare and a lot more interesting insights from Mitali. 

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Generative AI has made impressive strides in the last one year, taking the technology world by storm. Thanks to consumer- facing tools like ChatGPT, Bard, Claud and the like, there has been a huge perceptional change toward Generative AI – a technology that has been existing ‘silently’ for years! 

In fact, Generative AI or GenAI adoption has been faster than that of smartphones and tablets, according to Insider Intelligence. 

In the enterprise world, this technology has gained massive interest and acceptance in short order. A Box-sponsored IDC survey shows that two-thirds of executives have already deployed generative AI in some areas at their organizations, which is further evidenced by an IBM survey. About 42% of enterprise-scale companies surveyed by IBM report having actively deployed AI in their business. 

But what really lies beyond the hype? Are enterprises reaping real benefits out of their GenAI investments? We asked a few CIOs at the Tech Saga 2024 organized by CIO Klub Pune Chapter. 

“Business leaders are enamoured by the success stories of these technologies that often they tend to ignore the failures and the basic requirements that are associated with GenAI’Business leaders are enamoured by the success stories of these technologies that often they tend to ignore the failures and the basic requirements that are associated with GenAI.”

Shobhana Lele, CIO of Bombay Dyeing

2024 – A year of GenAI in production? 

2023, which could be considered the watershed year for GenAI, was all about experimentation and pilots, indicate studies. In a recent Gartner poll, about 45% of the 1,400 executive leaders surveyed reported that they are in piloting mode with generative AI. An IBM research estimates this figure to be around 40%. Interestingly, about 10% of them have put generative AI solutions into production and this figure is steadily growing. 

A sizable number of the enterprises in piloting mode are expected to shift their focus to practical implementation in the next one year– making 2024 a turning point in GenAI adoption. “For the 40% of companies surveyed stuck in the sandbox, I am confident 2024 will be the year of tackling and overcoming barriers to entry like the skills gap and data complexity.” Rob Thomas, Senior Vice President, IBM Software.

Catapulted by the increasing investments, the GenAI market size is projected to top USD 66.62 billion in 2024 with an anticipated yearly growth rate of over 20% through 2030.

Indian CIOs see more GenAI use cases evolving

Tech leaders in India are bullish about the prospects of the technology. India is already considered a front-runner in the adoption of GenAI, with as high as 81% of Indian organizations already integrating the technology into their operations (Elastic report).

What kind of promising use cases will emerge in 2024? Which industries will get touched the most? 

“GenAI use cases will grow quite exponentially in the coming years,” says Shobhana Lele, CIO of Bombay Dyeing, who is a passionate advocate of AI technology. She believes that the healthcare sector is poised to hugely benefit from GenAI. 

“Of all the mature use cases that will emerge, I find the technology’s impact on the Healthcare sector quite significant and far-reaching. It’s one sector with massive amounts of data and AI can accelerate use cases that are critical for the whole humanity, helping us find solutions for some of the pressing problems that have been around for decades,” she highlights. 

A NASSCOM study from 2023 states that the use of AI and data in healthcare might increase India’s GDP by USD 25–30 billion by 2025. 

Vinod Deshmukh, GM – IT, Haldiram Foods is already exploring various use cases of GenAI at the FMCG firm and believes that the FMCG sector stands to benefit significantly from the technology. “There are strong business use cases already emerging, which help FMCG companies improve product quality, predict outcomes, and increase the overall efficiencies,” he adds.

Generative AI in the banking and financial services sector, which is expected to create a massive USD 12 Billion market in the next 10 years, is another great opportunity. 

“Strong business use cases of GenAI are already emerging, which help FMCG companies improve product quality, predict outcomes, and increase the overall efficiencies.”

Vinod Deshmukh, GM – IT, Haldiram Foods 

“This is another sector that holds huge amounts of personal and sensitive data. AI will be critical in effectively leveraging this data to help consumers get the most out of their assets and investments while devising innovative ways of protecting their critical data,” says Shobhana.

Gen AI is now catalyzing a significant shift in the financial services sector, reports EY, with 78% of the firms implementing or planning Gen AI integration. Around 61% of financial institutions anticipate GenAI to have a profound impact on their value chain, enhancing efficiency and responsiveness, states the EY report.

Banking institutions across the globe are leveraging this technology to improve customer experience, provide personalized marketing and improve collections & recovery. Underwriting copilots are another big use case in the banking sector. 

Noteworthy is the fact that sectors that have been slow in adopting artificial intelligence are moving to a more proactive approach when it comes to GenAI. 

“GenAI is encouraging many brands to push the envelope – even those who haven’t yet considered AI use cases are exploring the possibilities of GenAI, says Vinod. He cites the example of manufacturing industry. In the manufacturing sector, GenAI will soon be leveraged in quality analysis, decision making and other core areas.”

Less than 20% of manufacturers have begun to implement AI technologies, reports suggest. However, GenAI seems to be moving the needle up, with the global market for GenAI in manufacturing expected to reach around $7 billion by 2032. 

GenAI challenges for CIOs

There are several challenges that tech leaders must tackle before they deploy genAI across key business functions. Data privacy and transparency are greater concerns for sure. So are the growing AI ethical challenges which require collaborative work across various stakeholders in the industry. 

Limited availability of AI skills is perhaps the top concern for CIOs today, Vinod emphasizes. “Access to the right skillsets is a challenge, especially for businesses in tier-2 & 3 cities. Tech leaders need to develop the right resources and technology capabilities to take this journey ahead,” he adds. 

The recent IBM Global AI Index highlights that nearly 35% enterprises report lack of skills for implementation is a big inhibitor for GenAI implementation. One-in-five organizations do not have employees with the right skills in place to use new AI or automation tools and 16% cannot find new hires with the skills to address that gap, the same research shows. 

To fill this gap in the current scenario, CIO will be expected to lead the task of reskilling and upskilling the existing workforce – especially because skills in data science, machine learning and MLOps are hard to come by. 

All in all, many CIOs want to take a cautiously optimistic path when it comes to taking GenAI to the next level. And reasonably so. 

“In my observation, many CEOs are gung-ho about implementing AI or generative AI, whereas the CIOs are a little cautious and apprehensive. There is a reason for this apprehension – Business leaders are enamoured by the success stories of these technologies that often they tend to ignore the failures and the basic requirements that are associated with GenAI,” Shobhana says. 

She believes that this perception leads to a lot of pressure on CIOs to start using these technologies with the expectation that it’s going to be successful. “But, every CIO has the responsibility to make the organization aware of AI/GenAI’s basic requirement – the relevant data sets, skillsets and the support. So, it’s a tightrope walk for the CIO,” she sums up. 

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