Artificial intelligence may be many things but to businesses and enterprises, its real value lies in how well it can be capitalised. The digital transformation possibilities are staggering, and as AI innovations leap out of research labs and go mainstream, organisations are devising an enterprise-AI strategy as the next plan of action.
Over the last two years, India has seen frenetic development in this area with tech behemoths like Adobe, Microsoft and NASSCOM speeding up innovation by setting up centres of excellence (CoE) in India which operate as labs or accelerators to nurture innovation and foster a thriving AI ecosystem. NASSCOM also inked an agreement with government think-tank NITI Aayog to collaboratively foster applied research, accelerating adoptions and ethics, privacy and security, the statement added.
From state and union governments to tech giants, CoEs are the go-to formula to embed an AI strategy and build enterprise AI services. These are one of the fastest-growing market segments with an annual growth of more than 100 percent, as projected by a research. However, their findings also indicate that as Enterprise AI is not one single market, sizing the total market can also be misleading. Its operational impact will be seen in service delivery capability and specific use cases. As the market matures, AI will have the potential to disrupt and replace enterprise architectures and enterprise software.
CoE And AI Labs: Building Blocks Of A Thriving AI Ecosystem
Earlier this year, San Jose-based software giant Adobe announced that they would be setting up a dedicated AI centre in Hyderabad. The benefits will be manifold, concluded Adobe CEO Shantanu Narayen, emphasising on how the abundance of tech talent in Hyderabad, backed by a pro-business stance will help them grow.
Earlier in July, US chip major Nvidia joined hands with the Council of Scientific and Industrial Research (CSIR) to set up an AI Innovation centre in New Delhi. The centre has been set up to provide the industry with a design and implementation environment for the development of AI-based applications. According to a CSIR statement, the centre will provide a platform for developing AI systems to provide solutions in healthcare, natural resource management, food production, security and transportation.
Meanwhile, NASSCOM set up a Centre of Excellence for Data Science and Artificial Intelligence in Bengaluru in collaboration with Karnataka government in July. NASSCOM President Debjani Ghosh was cited by news sources, saying the centre is the step towards building data sciences and AI capabilities to power global product solutions from India.
Also, Bharti Airtel, one of India’s leading telecommunication companies was in the news to set up an advanced digital innovation lab to produce solutions in emerging technologies such as IoT, augmented reality, virtual reality as part of its broader business strategy to develop capabilities in next-gen tech. News reports indicate the digital lab project is being led by Harmeen Mehta, global chief information officer, Airtel.
How CoEs Accelerate Development And Push Ecosystem Enablement
- For enterprises to emerge as front-runners in the AI race, they have to shape product development and build AI applications around their data supply. Setting up a CoE is one way to go about after the actionable agenda by developing POCs around key areas.
- CoEs provide a great opportunity to connect with data scientists, researchers, academia and startups to build solutions for their portfolio of technologies
- Given that organisations currently lack maturity around AI and are yet to develop a formalised AI practices, CoEs help enterprises build practices with AI-specific partners. For example, TCS set up an AI Centre of Excellence in collaboration with Intel to accelerate adoption of AI solutions in September 2017. According to V Rajanna, vice president and global head, Technology Business Unit at TCS, this move will help the company reimagine products and services around AI, drive revenue and improve customer experience.
- Even though the market is inundated with PoCs, they lack insights and commercial applicability. Given how enterprises are wary of vendor lock-in, and depend on platform services from IBM, SAP, AWS, Microsoft which have formalised AI platforms, a dedicated CoE helps in building in-house capabilities and at the same time reduces dependencies on pre-trained ML solutions provided by leading tech giants.
- CoEs can also drive knowledge management gradually, build knowledge graphs that allow enterprises to leverage their data assets across organisations just in a way web giants Facebook or Google do it.
- Since AI is not plug-and-play but has a data-centric approach, a dedicated CoE or an AI lab will also give the organisation an opportunity to utilise dark data, which is mostly underutilised.
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