The Blueprint for Success with Gen-AI

GenAI is changing the way we do business. The implications of GenAI are far-reaching- its reshaping industries, redefining user experiences, and offering unprecedented capabilities. As the boardroom remains abuzz with this hype, the ambiguity regarding the adoption of the technology, charting a concrete roadmap, and measuring its success permeates.?

In this article, we provide five recommendations that will guide the C-suites while making any Generative AI-related decisions.?

1) Mindset: Our first recommendation is to precipitate a mindset shift, top down and across the organization around the potential of GenAI. There should be positive anticipation to leverage the technology coupled with the apprehension of being left behind should you fail to keep up with the pace of innovation. Think of GenAI as the booster dose to long existing capabilities around AI, Data and Analytics. In that sense, it is not new. It is rather a shift that has broken some barriers for organizations towards becoming data driven, specifically where progress was hampered due to poor quality data. GenAI enables organizations to leverage vast amounts of data collected over a period of time, whether structured or unstructured, good or average quality, and derive value from that. Hence, downplaying the hype means neglecting the future-readiness of the organizations. Every function and line of business should be asked to provide a plan suggesting how they will reduce costs, improve efficiencies, grow faster and create a competitive differentiation in the product/service they have by leveraging GenAI.?

2) Structure: Organizations should not leave GenAI efforts to their engineering teams alone. Instead, they should encourage business and engineering teams to jointly share the responsibility. This requires the setting up of “Lighthouses”. A “Lighthouse” is a multidisciplinary team of domain experts, designers, consultants and engineers. They come together and identify opportunities through a series of design thinking workshops. They will have the “mandate to innovate and license to deliver,” These need to be set up at each function/ LOB (Line of Business) level, supported by a core engineering team. For example, a “Lighthouse” for a customer service function will be a mix of top agents, designers, consultants and engineers. Domain understanding and empathy-led user journeys are key to identifying areas where GenAI should get deployed on priority. Governance should be established on the progress of the plan, funding required, and ROI generated. Governance should be at two levels - at a function/LOB level as well as at CXO level. CXO level governance will also enable sharing of best practices, replicable successes and most importantly, drive organization-wide prioritization of use cases.?

3) Focus on creating Business Value: GenAI can create an impact across product and service experience, operational efficiencies, and growth. The lighthouses should undertake a series of design thinking workshops and generate a log of ideas and potential use cases. These use cases thereafter should be mapped and prioritized based on the business value and ease of implementation.?There are two frameworks given below.

The 2 x 2 framework across “Ease of Implementation” and “Business Impact” is self explanatory. Business impact should include a multiplier on the durability of the competitive advantage.

The second framework shows the intersection of growth, product/service experience, and operational efficiencies. Logically, use cases falling at the intersection of all three circles should be the most valuable. A tip here: Prioritize use cases that help your customer’s clients improve their revenues (in a B2B context). For instance, as a SaaS CRM provider, explore how GenAI can help your customers get a better view of heat maps.?

Additionally, the way we measure success needs a shift. Instead of just looking at "Proof of Concepts" (POCs) which are initial tests or demonstrations of a solution – we should focus on the real-world value. We should look at how these solutions, when implemented, reimagine businesses in real, everyday scenarios.?

4) Adopt “human-in-the-loop” approach: ?Current? messaging around GenAI promises utopia. However, the technology capabilities may not have evolved to that extent. Hence, leveraging technology to improve the performance of the teams is the approach that we strongly suggest. This approach will have multiple benefits.?

• First, it will bring faster results. Instead of waiting for the perfect technology solution, we can have faster outcomes. With humans overseeing or assisting, it's often easier to adapt and make on-the-spot decisions.?
• Second, it will reduce the change management challenges. When people feel involved and essential in a process, they are more likely to support it. They might resist an entirely automated system, feeling it could replace them. However, when they are a part of the process, they can see the benefits more clearly and are more willing to adopt new methods.
• Third, it will definitely provide a competitive advantage. Partnering with people can give a unique edge to a business, while leveraging the benefits of technology. Humans bring creativity, intuition, and personal experience that machines don't have. When combined with the speed and efficiency of AI, this human touch can drive better unit economics – which means better value and efficiency for each unit of work or product.?

This approach is what we call as “Human in the loop” approach and should be an

integral design principle of Gen AI initiatives.?

5) Optimize GenAI spending: The world of GenAI, with its vast potential and dynamic applications, necessitates careful decision-making when it comes to the solution design. The right solution design enables crafting of a strategy that is both smart and holistic. This requires deliberation on 5 aspects.?

• Choosing the right pricing models.
• Choosing the pathway for achieving the desired results. For example, one can query a huge bucket of data and information using natural language but this can prove to be very expensive. Alternatively, optimized pathways including drop down menus and standard summaries can be created before leveraging the GenAI models. Even with GenAI, smaller specialized models trained on organization’s business context and data should be built as compared to leveraging general purpose models.?
• From the data source standpoint, data preparation can be better on the backend to provide not only better results but with lesser usage of compute.?
• Fourth, a decoupled architecture should be created with an assumption that this space will follow Moore's law. Costs will rapidly go down simultaneously and innovation on sharper and more contextual models will happen at a fast clip. Organizations should be able to plug in new capabilities seamlessly as this evolution happens.?
• Fifth and last, guard-rails should be put so that mistaken use of undisciplined queries is avoided. One wrong query can lead to significant spending.?

In summary,, as we stand on the cusp of this new era, navigating the contours of the GenAI revolution will require strategic foresight, adaptability, and a commitment to continual learning. Only then can we harness its true potential and ensure that the hype translates into tangible benefits for all. More importantly, the first mover advantage will be a game-changer for the adoption of GenAI. So, our advice would be to move fast, purposefully and decisively.???

Authors:

Rahul Shah is an alumni of two of the most prestigious universities of India - IIT and IIM-A. He has had 25+ years of experience and works as a business head for the Searce JAPAC region. He has led design and technology led transformation initiatives for a couple of decades across some of the largest GSIs. Rahul has worked on multiple multi-million dollar digital transformation engagements across Asia Pacific, Middle East & Africa leading digital, legal and business process transformation initiatives.

Dr. MuthuKumaraswamy B is an alumnus of one of the most prestigious universities of the country - University of Madras. He works as Associate Director Applied AI Practice at Searce with a passion for driving digital transformation and a proven track record of spearheading complex initiatives. He brings a unique combination of strategic vision, technical proficiency, and exceptional leadership skills to help organizations thrive in the digital age.

Tanvi Talesara is a Cloud consultant in India region at Searce. Tanvi offers holistic support to our clients by working closely with them as well as the internal teams to ensure we can drive smarter, faster, better outcomes for our clients. Her passion for technology coupled with a ‘solve differently’ mindset has been value-adding for Searce.?