Note: This is the Second Part of a three-part series of our study ‘State of Enterprise AI In India 2019’ brought to you in association with BRIDGEi2i. Stay tuned for Part III.

Check Part I of the three-part series here.

Check Part III of the three-part series here.

Business models — Niche Players, Captives, Large AI Consultancies

The AI Player landscape in India can be divided into 3 ways — mega ISVs, captives, and AI consultancies. 

1.Mega ISVs

Mega ISVs — Microsoft, Google, AWS, IBM, Intel, NVIDIA have become foundational to AI by providing the building blocks and computational resources for driving AI applications. These top innovators are also the AI leaders, offering solutions that can handle functions like sentiment analysis or speech recognition with minimal infrastructure. The mega ISVs have built a formidable ecosystem by taking a platform approach and supplying the underlying components that form the building blocks for AI-led innovation. 

• Hardware: GPUs, ASICs which complement general-purpose processors CPUs
• Deep Learning Frameworks: TensorFlow, BigDL, MXNet, Caffe, PyTorch, PaddlePaddle 
• Toolkits for AI Deployment: OpenVINO, Amazon Sagemaker, AutoML

2.Captive Units of Global IT corporations 

In India, GICs/captives have become a potent force for AI innovation. With their scale, agility, highly-skilled team, an enabling infrastructure, a roadmap, and an innovation mindset — captives are making the most of the AI wave by not just overhauling traditional operations offshored but building disruptive solutions. Many large global organizations with GIC presence in India are strategically building prototypes in a relatively low-risk environment that can be implemented into the broader organizations. Some captives have built innovation centers to experiment with low-level PoCs. 

• WalmartLabs: Builds new platforms and software solutions to support e-commerce and store businesses globally
• Tesco Labs: Tesco Bengaluru center was set up in May 2004 to enable standardization and build centralized capabilities and competencies which can be leveraged across the Tesco Group. With a technology focus on Big Data Analytics, AI, cloud, AR & VR, the innovation lab applies analytics and AI for Tesco operations. 
• MasterCard Labs: Set up in 2017, Mastercard Labs in India is the company’s ninth lab in the world and the second in the Asia Pacific (following Singapore). Mastercard Labs work with financial institutions and merchant partners and the Fintech community to identify and experiment with future technologies in a few key areas, including digital payments, data solutions, financial inclusion, alternative payments, and safety and security. 

Many non-traditional companies and Indian conglomerates have also turned into top innovators like Siemens, Bosch, Reliance Communications, Tata Group and automakers like Nissan, Mahindra & Mahindra who are reinventing the wheel by setting up dedicated CoEs.

3. Deep-Dive on AI Consultancies 

AI Consultancy stack can be divided into three categories:

• Large tech Consultancies led by the Big 4 and Accenture with revenues < $100 Million
• End-to-end service providers like Mu Sigma, Fractal Analytics, NTT Data, KPMG, Capgemini, Cognizant, AbsolutData, NEC drawing revenues ($20 – $100 million)
• Niche AI Service firms focused on AI-led business transformation like BRIDGEi2i, Cartesian Consulting, Tech Mahindra, Synechron and Virtusa > $20 million powering business innovation with domain agnostic solutions. 

How AI Consultancies Solve Specific Business Problems (enablers)

1. Given the current stage a company is in — whether it is enabling data-driven processes or looking to push the current system to the next edge, AI Consultancies play a pivotal role in operationalizing AI. 
2. AI Consultancies bring on-board specialist teams of data scientists, developers, consultants, product managers who can deliver end-to-end AI solutions. 
3. Organizations today prefer the pay-as-you-go model where every service is compartmentalized and available to them as per their consumption. Solutions/accelerators from service firms can also be viewed as a scalable plug-and-play format. 

AI consultancies have also been early players in offering AI-based solutions and accelerators — pre-built customizable solutions that significantly reduce the time-to-market and also lower the entry barriers for organizations looking to stay ahead of the game. These consultancies are bringing forth a set of distinct business agnostic tools built for specific narrow business problems. 

Proprietary AI accelerators coupled with consulting expertise, can deliver contextual AI-powered insights wherein self-learning algorithms provided by the accelerators can map relationships across business metrics, derive correlation, and detect anomalies to provide real-time actionable insights. BRIDGEi2i’s proprietary AI accelerators: Watchtower | Recommender | Optimizer | Converser, enable the democratization of analytics insights to drive faster and more accurate business actions for digital transformation outcomes.

• The Watchtower provides real-time KPI monitoring and alerting through surveillance systems
• The Recommender aids effective decision-making by providing personalized insights
• The Optimizer helps businesses simulate and test scenarios for better forecasting and planning, optimal spend allocation and effective utilization of resources
• The Converser makes the entire experience real by leveraging its conversational AI and interactive experiences in conjunction with Watchtower, Recommender, and Optimizer.

Suppose for a Customer Experience situation, a firm wants to ascertain how to keep customers satisfied. We can deploy Watchtower to predict which customer will escalate his grievance to the Customer Care; the customer care executive will then be given a set of recommendations by the Recommender to solve his issues. The end result is a happy customer.