AI For Better Tomorrow: How Machine Learning Can Solve Industry Challenges

A shortage of AI-specialised roles is evident, with a demand-supply disparity ranging between 60 per cent and 73 per cent for positions.

The AI landscape is competitive, and often many market solutions rely on established innovations.

Source : Possessed Photography/Unsplash

By Rahul Paith

Artificial intelligence (AI) has emerged as a transformative force, revolutionising industries worldwide with its capabilities. As AI adoption surges, both companies and nations are intensifying their efforts to develop robust AI capabilities. India is making significant strides as a global leader in AI, with its market projected to reach $7.8 billion by 2025. 

Much of the cutting-edge innovation in the AI ecosystem is being led by startups, that are agile and focused on solving industry problem statements with their innovative approaches. While there are tremendous opportunities for startups to capitalise on, there also are challenges. AI-driven ventures require a unique set of resources and support structures to thrive. Accelerators and incubators play a pivotal role in bridging gaps and propelling AI innovation.  

Addressing AI Skills Gap 

AI has become a competitive edge for businesses, with 37 per cent of organisations around the world deploying AI solutions — a staggering 270 per cent increase from four years ago. Despite this growth, companies face a significant skills gap in AI. The most critical roles needed include AI builders (who create and deploy AI solutions) and AI translators (who bridge the gap between technical and business aspects of AI solutions). 

A shortage of these roles is evident, with a demand-supply disparity ranging between 60 per cent and 73 per cent for positions such as machine learning (ML) engineers, data scientists, DevOps engineers and data architects. Here’s where accelerators and incubators become invaluable.  

They create ecosystems where startups can share resources, including access to highly skilled professionals. Within these ecosystems, startups often lend their expertise to one another at a negotiated cost, making high-end talent more accessible. The collaborative approach allows startups to leverage top-tier technical knowledge without bearing the entire financial burden themselves. 

Reducing Operational Costs Through Resource-Sharing 

Accelerators and incubators play a crucial role in resource sharing, which is vital for reducing operational costs and driving startup growth. The financial strain of acquiring advanced computing power and specialised software can be daunting for AI startups.  The high salaries of top-tier AI professionals can be prohibitive for emerging companies. 

To address the financial challenges faced by AI startups, incubators and accelerators connect them with a highly skilled and cost-effective talent pool from tier 2 and tier 3 cities. This emerging workforce, located in cities such as Ahmedabad, Kochi, Indore, Coimbatore and Jaipur, plays a vital role in managing essential tasks like data entry, data annotation and data labelling. By leveraging this talent, startups can focus on core innovations while optimising operational costs.  

It helps startups achieve a more efficient and balanced allocation of resources and contributes to the development and growth of skilled professionals in these rapidly evolving regions.  

About 70 per cent of India’s talent is concentrated in Tier-1 cities, Tier-2 and Tier-3 cities and they are increasingly recognised as key hubs for data science and AI, reports Nasscom, offering valuable opportunities for both startups and the broader industry. 

Offering Early Access To Technologies 

The AI landscape is competitive, and often many market solutions rely on established innovations. However, startups supported by accelerators and incubators often gain access to emerging technologies still in development. This early exposure is crucial for staying ahead of industry trends and significantly speeding up product development and market entry. By integrating advancements before they become mainstream, these startups minimise the risk of redundancy, ensuring their solutions remain relevant and innovative. This strategic edge strengthens their market position, making them more competitive. 

Early access to cutting-edge technologies also enables startups to collaborate with leading researchers and technologists, fostering an environment of continuous learning and adaptation. This not only enhances their internal capabilities but also opens up opportunities for co-development and strategic partnerships, further solidifying their market presence. Such collaborations can result in the creation of proprietary technologies and intellectual property, giving these startups a unique advantage over their competitors. 

Enhancing Funding Prospects 

Securing funding presents a significant challenge for AI startups due to their high capital requirements and the associated risks, which often deter investors. However, accelerators and incubators substantially improve funding prospects. Startups involved in accelerators raise 50 per cent to 170 per cent more from investors and have higher survival or acquisition rates suggests a Harvard Business Review report as compared to those that applied but were not accepted. 

Accelerators and incubators bridge the funding gap by providing tailored support to navigate the complex funding landscape and connecting startups with a broad network of global investors. It increases the chances of successful capital raising. Such support is particularly critical for AI startups, which, due to their high development and operational costs, often require more funding. By leveraging these opportunities, accelerators and incubators enhance the financial viability of AI startups and contribute to their long-term success and sustainability in a competitive market. 

Leveraging Advanced Tools & Resources 

Accelerators and incubators play a crucial role in providing startups with access to advanced tools and platforms that might otherwise be inaccessible. Cloud platforms such as Microsoft, Amazon Web Services (AWS) and Google lead in offering a comprehensive ecosystem of infrastructure, tools, libraries and frameworks. These platforms are pivotal in managing data, applying AI/ML techniques and scaling products. By 2027, IT spending on public cloud services is forecasted to exceed USD 1 trillion, reports Gartner. 

In the Indian market, these cloud platforms have been instrumental in fostering innovation by offering end-to-end solutions that support experimentation, accelerate development and enable scaled deployment. Gartner projects that over 50 per cent of enterprises will adopt industry cloud platforms by 2028 to enhance their business initiatives, reflecting the growing role of cloud computing as a business necessity rather than just a technology platform. But the need of the hour is for homegrown capabilities that can bring down the cost of these advanced solutions, making them more accessible to a broader range of startups and enterprises. 

To continue driving AI innovation, it's imperative for stakeholders—governments, investors, and industry leaders—to invest in and support these accelerators and incubators. By doing so, we can ensure that the next wave of AI breakthroughs is not only possible but realised, shaping a future where technology enhances every aspect of our lives.  

(The author is the CEO of MATH)

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