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Predictions Series 2022: AiThority Interview with Hemanth Manda, Head of Strategic Partnerships at IBM

Hemanth Manda, Head of Strategic Partnerships at IBM

Welcome to our Interview Series. Please tell us a little bit about your journey in this industry and what inspired you to start at IBM?

I started at IBM 16 years ago as an architect for Data and AI Consulting and held several positions on my way to becoming the executive director of strategic partnerships. What continues to inspire me about IBM is the partnerships and relationships that we have in place. In my role, I see how important building a robust ecosystem is and how our partnerships help us increase AI adoption across the industry at large. We are working to equip companies with the AI technology that they need to create a more successful business and that inspires me every day.

What are your core offerings in the embeddable AI suite and which markets are you currently targeting with your product?

Embeddable AI is an initiative at IBM that includes a set of flexible, enterprise-grade AI products that developers can easily embed in their applications to provide an enhanced end user experience. IBM’s embeddable AI portfolio includes two main types of products that can be accessed in different ways to meet the unique needs of different users — via flexible libraries and APIs or applications.

We recently launched three new software libraries — Watson Natural Language Processing, Watson Speech to Text and Watson Text to Speech — that make it easy for developers to embed NLP and speech capabilities into their applications without having deep expertise in AI or machine learning.

These new libraries expand IBM’s existing portfolio of embeddable AI for partners, which includes our IBM Watson APIs on IBM Cloud and applications such as IBM Watson Assistant, IBM Watson Discovery, IBM Instana Observability, and IBM Maximo Visual Inspection. This will make up our portfolio, for now, with the intention to grow and launch more Watson Libraries in 2023.

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How important is embeddable AI software in the current context of IT and automation?

I can’t think of a single industry that AI won’t transform in the next several years. Every application and solution — from CRM, ERP, and cybersecurity to HR, e-commerce, and process automation — will have AI built into them. Some companies may be able to build their own AI from the ground up, but it requires significant investments, resources and time. In fact, IBM’s 2022 Global AI Adoption Indexfound that the skills gap remains a significant barrier to AI adoption, with 34% of respondents citing limited AI skills, expertise or knowledge hindering successful AI adoption. So many companies need a partner like IBM to help them embed cutting edge AI into their applications.

Our goal with the embeddable AI initiative is to offer our IBM Watson technology in a way that application developers can easily embed in their application without deep expertise in AI or machine learning. So internally we studied products that developers love, and found a few common factors. Developers need to be able to start getting value from technology in hours, and they want a modular architecture so different capabilities can be put together quickly, making it faster to implement interesting AI use cases. So we developed a set of embeddable AI libraries with a great developer experience that are used internally by our own development teams across many of our popular software products including Watson Assistant, Watson Discovery, Cloud Pak for Watson AIOps and many more. At IBM, we saw significant time savings from our development teams by using the embeddable Watson NLP library versus building AI from scratch.

For IBM, the embeddable AI initiative represents a huge opportunity. We are able to bring the best of IBM Research innovation and open source to our partners and give them a core set of AI technologies to help them get more intelligent application experiences into the market faster.

Which companies benefit the most from investing in embeddable AI? What distinguishes your solution from others in the market?

Many companies across industries can benefit from embeddable AI, but we’re really focused on our IBM Ecosystem partners, specifically independent software vendors (ISVs). We listened to their pain points, and are bringing significant learnings and experience from our own internal journey to embed AI into our own IBM Software.

The pace of innovation happening in AI across the industry is incredibly rapid and would be nearly impossible for every company to keep up with on their own – it requires continued investment that is hard to sustain. With IBM’s embeddable AI initiative, ISVs will now be able to bring novel AI solutions to market faster at reduced costs with fit-for-purpose embeddable AI. Embeddable AI enables our partners to infuse the best of IBM Research technology built on an open-source framework. This same technology powers the cutting-edge IBM products such as Watson Assistant, Watson Discovery, Watson Knowledge Catalog and Cloud Pak for Watson AIOps.

IBM’s embeddable libraries offer a lot more flexibility compared to whats available through other providers. The new libraries include a wide variety of models and runtime configuration options that allow ISVs to pick what they need that best suits their use case. And most importantly, they can embed and deploy these libraries anywhere, including in their own data center, at the edge or on any public cloud of their choice. This is critical for ISVs who want flexibility and to avoid vendor lock-in.

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Please elaborate a little bit about the IBM Ecosystem and how it has accelerated the pace of machine learning-centric innovations in the recent years.

The IBM Ecosystem is a network of tens of thousands of partners of all types, digital marketplaces, developers, and more, leveraging joint strengths to use hybrid cloud and AI to solve some of the most complex challenges in business and society. IBM wants its partners to be the best in the industry at establishing a hybrid cloud architecture and an AI footprint for clients. Embeddable AI is provided in a form factor that caters to a variety of partner requirements including applications, APIs and libraries, to make it easier and faster for our partners to build with AI. With our embeddable AI initiative, we are working with partners to accelerate the pace of adoption of AI and machine learning to deliver better end-user experiences.

What role would embeddable AI play in the area of application security, and is it relevant to any anticipated security trends and challenges that could be facing the industry in 2023?

AI is helping under-resourced security operations analysts stay ahead of threats. AI is able to curate threats from millions of resources including, research papers, blogs and news stories, AI technologies like machine learning and natural language processing provide rapid insights to cut through the noise of daily alerts, drastically reducing response times. IBM Research is working on some cutting edge AI technologies that we expect to become part of embeddable AI portfolio in the near future.

The last two years have accelerated digital transformation for businesses of all sizes and stature. What has been the biggest lesson for you?

The pandemic has demonstrated how important data and AI is for businesses. During Covid businesses had to be flexible and agile, and now they are dealing with an increasingly complex operating environment with lots of unforeseen disruptions. AI can help companies streamline their processes, provide a better employee and customer experience, and automate mundane tasks. IBM’s new embeddable AI libraries have a lot of powerful use cases to help our partners build better, more powerful experience to address some of these challenges. For example, a developer could use the IBM Watson Natural Language Processing library to provide knowledge workers answers in real-time from a large corpus of information, augmenting awareness and increasing productivity.

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How important is it for a technology company like IBM to build a world-class company culture where the best product development talent thrive?

People are the key to innovation. If we want to have a culture of innovation we have to make sure that our people are taken care of and supported. Our culture allows for people to share new ideas, to try to them out and gives new ideas room to fail. I think the embeddable AI initiative represents a great example of many different teams within IBM — across IBM Software, IBM Research and IBM Ecosystems — coming together to develop a new approach to solve a common challenge for ourselves and our partners.

Is there an event/ conference or podcast that you have subscribed to consume information about B2B technology industry?

Yes, I attend quite a few industry conferences and subscribe to a number of podcasts including Exponent, a16z, Acquired, TechCrunch & The Cube.

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

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Hemanth Manda heads strategic partnerships for IBM Data & AI organization. In his current role, Hemanth manages a team of 25+ product and partnership executives. He has broad experience in technology and software industry spanning several strategy and execution roles over the past 20years. Previously,  Hemanth  lead a team of product managers responsible for simplifying & modernizing IBM’s Data & AI portfolio and helped launch a new platform offering “IBM Cloud Pak   for   Data” .Among   other   things,   he   is   responsible   for rationalizing and streamlining Data and AI portfolio at IBM and delivering new platform wide capabilities through “Cloud Pak for Data”. Prior to that,  he  also served as a chief of staff to Rob Thomas, General Manager of IBM Data and AI and lead the Business Development team responsible for acquisitions,  divestitures  and strategic partnerships at IBM’s Analytics and middleware business units.  There he worked on developing division’s buy side M&A strategy,  sourcing  deal flow, influencing valuation and terms, executing   due   diligence,   developing   integration plans, and negotiating transactions. Hemanth likes to play basketball on weekends and lives in Dallas with his wife and 2 kids.

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