AiThority Interview with Rohit Tandon, GM for ReadyAI and MD at Deloitte Consulting LLP

Please tell us about your role and the team/technology you handle at Deloitte? How did you arrive here?

My team and I help clients accelerate AI adoption and then scale AI deployment in the enterprise to drive real measurable business results.In my professional journey of 25+ years, I have held leadership roles across Strategy, Analytics, Process, People Management and Technology working at blue chip companies like Accenture, GE, Genpact, IBM and HP. I have been a Business Leader with a $4.5Bn Revenue; CIO for Asia, Pacific and India for another $100Bn+ company; a CIO for the most diverse global region. My focus has always been to help companies transform, optimize and get business impact from their investments in Data and Technology.

Could you tell us the evolution of AI-as-a-Service and the industries that benefit the most from leveraging these applications?

Adopters across all industry segments are increasingly confident of AI technologies’ ability to drive value and advantage. The human-machine collaboration is taking organizations to new heights. Deloitte calls it the “Age of With”!

However, despite its attractiveness, many companies are stuck in the experimentation phase of AI. The current market challenges that block businesses from scaling AI throughout their organizations range from a dearth of high-quality resources with AI knowledge to the high cost of continuously monitoring and managing AI solutions. AI-as-a-service provides a customizable combination of industry and domain expertise, AI technology skillsand managed services to help these businesses become AI-fueled organizations.

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What is Ready AI? Could you explain and tell us how you tackle the perennial challenges of delivering AI-as-a-Service to your customers?

ReadyAI will bring together skilled AI specialists and managed services in a flexible AI-as-a-service model designed to help clients scale AI throughout their organization. ReadyAI offers capabilities such as data preparation, insights and visualization, advanced analytics, machine and deep learning, machine learning deployment and model management, and MLOps. It also provides accelerators such as data and insights, assets and use cases, and platforms and tools that help organizations scale their AI projects.

Some of the challenges we try to solve for in delivering AI-as-a-Service include focusing on the business impact of client’s objectives, transitioning from AI experiments to also scaling and optimizing solutions, and finally, avoiding the trap of AI becoming a solution looking for a problem.

How do you help lagging companies in AI adoption?

Organizations tend to get stuck in a plethora of disparate pilots as they struggle to scale AI. Disconnected processes, tools, and governance present scaling challenges that bog down efforts to become an AI-centric organization—all while speed is of the essence. Without the right expertise and tools, venturing into AI can be a very slow and frustrating experience. What an aspiring AI-centric organization needs, first and foremost, is to make sure AI efforts are aligned with business strategy and goals. ReadyAI provides flexible and scalable capabilities these companies need to successfully become AI-fueled organizations. We help set up systems and processes so models can be reviewed and monitored on an ongoing basis. We provide next-gen assets, preconfigured solutions, and platforms to translate AI insights into trustworthy performance. We also help implement ethics governance for AI – what we call Trustworthy AITM.

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Do you think the pandemic has accelerated adoption of AI across organizations? What are the other factors driving the adoption of AI in the industry?

The pandemic has accelerated adoption of AI across organizations. Deloitte’s State of AI in the Enterprise, 3rd edition surveyed executives about their companies’ sentiments and practices regarding AI technologies. We found:

Sixty-one percent (61%) say AI will substantially transform their industry in the next three years.

Adopters are making significant investments with 53% spending more than $20 million over the past year in AI technology and talent.

What kind of skills in data science and engineering should organizations look to hire to grow their aspirations with AI and ML?

Companies require a broad range of skills for their AI initiatives across data science, IT operations and user experience (UX) – data scientists, ML engineers, cloud engineers, data engineers, visualization experts, and domain experts. Unfortunately, a talent skills shortage means that many companies struggle to find the resources and capabilities they need.

Tell us more about IT operations and the kind of resources companies need to fuel their AI goals?

Organizations that want to scale AI across all areas must focus on implementing a set of standards and a framework to create production-capable AI building blocks. It is not enough to focus on sophisticated model development. Data science and AI/ML modelers need to be in lockstep with MLOps engineers, data engineers, and process experts. It requires a diverse and cross-functional team.It will not be possible to industrialize AI if the reliance is on a few talented practitioners in niche techniques and technologies; industrialization will require the coming together of a varied mix of talent and technologies. This is where concepts such as MLOps and DevOps come in – automation (as opposed to siloed custom dev); deployment (proliferation, as opposed to one-time use); process (integration, testing, and releasing); and infrastructure considerations.

Hear it from the pro: What is your prediction on the evolution of AI Machine Learning in the world of Cloud computing and Analytics:

Currently the hype that has developed around AI is leading to success being defined as ticking the box in adopting the two letter acronyms AI/ML and demonstrating something innovative. Very soon the focus will shift to asking the business questions around benefits realization for companies and their customers. That’s when the true power of AI/ML will be focused and go above and beyond the hype that is currently in the spotlight.

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Thank you, Rohit! That was fun and we hope to see you back on AiThority.com soon.