[00:00:00] Is your organization prime for the transformative journey into Gen. AI?
[00:00:07] Well, in an era where artificial intelligence is no longer a distant marvel but rapidly becoming
[00:00:13] a close ally.
[00:00:15] Enterprises across the globe are evaluating their readiness to embrace this technological
[00:00:20] leap.
[00:00:21] Joining me today is Sanjay Jain.
[00:00:23] He is the Chief Business Transformation Officer at WNS.
[00:00:28] And they are a leading light in business process management solutions.
[00:00:33] But I've invited him on today to leverage his insights from the comprehensive survey conducted
[00:00:38] by WNS and the Everest Group that recently set off my TechSpy descents.
[00:00:44] And it's my hope that today we're going to shed light on the pivotal aspects of enterprise
[00:00:49] readiness for Gen. AI implementation because as industries grapple with the challenges
[00:00:55] of technology, data, process and people readiness, I want to explore the sectors leading this
[00:01:01] charge.
[00:01:02] The strategic moves to combat talent shortages and also the paramount importance of ethical
[00:01:09] AI use and responsible AI.
[00:01:13] So Sanjay's insights promise to unravel the complexities and also her order future
[00:01:18] where Gen. AI is not just adopted but is integral to enhancing customer experiences
[00:01:25] and operational efficiencies across vast sectors.
[00:01:29] But before we get today's guest on, I need to pay the bills.
[00:01:32] We've got a huge podcast hosting fee to pay for when we're releasing 30 episodes a month
[00:01:37] and this month I've partnered with a company called Kiteworks.
[00:01:42] Now legacy MFT tools are dated and lack the security that today's remote workforce
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[00:01:52] their sensitive data at risk.
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[00:02:42] that's kiteworks.com to get you started today.
[00:02:46] So buckle up and hold on tight as I beam your ears all the way to Mumbai in India
[00:02:51] where today's guest is waiting to share his story.
[00:02:55] So a massive warm welcome to the show Sanjay, can you tell everyone listening
[00:03:00] a little about who you are and what you do?
[00:03:02] Neil thank you for inviting me to your show and I am the Chief Business
[00:03:07] Transformation Officer of WNS and in my current role I'm responsible for
[00:03:12] ensuring that all of our client businesses that we manage for them
[00:03:15] are transformed with the right use of process innovation,
[00:03:20] technology interventions and analytics.
[00:03:22] And being with WNS for almost 20 years prior to WNS I was actually a serial entrepreneur
[00:03:29] I had set up three fairly successful firms which got sold
[00:03:33] and then early on I started my career with a company called CMMC
[00:03:36] in a typical program management system architect role
[00:03:39] delivering very well known mission critical applications
[00:03:43] and from an education perspective I'm an electronics and communication engineer Neil.
[00:03:48] Fantastic, it's a pleasure to have you join me on the show today
[00:03:52] and there's so much I want to talk with you about
[00:03:55] because at the moment everyone's going crazy about generative AI
[00:03:59] they have done for the last 18 months but what we're seeing now is
[00:04:02] people now know how it works and they're starting to get over there
[00:04:05] maybe fair or apprehension about it
[00:04:08] and exploring how they can use it in their business
[00:04:11] and one of the things that put you on my radar was a recent survey
[00:04:15] you did on generative AI in I think it was a CXM survey
[00:04:19] supported by WNS but can you tell everyone listening a little about that survey
[00:04:24] and also how it indicated a significant level of readiness
[00:04:29] for generative AI implementation among enterprises
[00:04:32] and from your perspective what factors are driving this readiness
[00:04:37] perhaps it vary across industries because there's so many great insights in that survey isn't there?
[00:04:42] Yeah, so let me have a quick brief on the survey
[00:04:45] it was done in collaboration with Everest and about 200 organizations
[00:04:49] were surveyed around various aspects of adoption, readiness, utilization,
[00:04:55] risks, types of things and we got some fairly insightful outcomes as part of the survey
[00:05:02] which interestingly correlates with what we are seeing actually on the ground
[00:05:05] because WNS has been deploying many use cases in last 12 months
[00:05:10] across the industry segments that you work with
[00:05:13] and interestingly what this survey told us correlates very well with our experience of deploying this solution
[00:05:22] so as I said based on our experience of deploying this multiple gen AI powered solutions
[00:05:29] broadly four key factors are driving enterprise readiness for generative AI implementations
[00:05:35] and these are the first is actually the technology readiness so you know which includes
[00:05:40] availability of adequate computing power, ability to scale on demand and cloud-based infrastructure
[00:05:47] capacity. The second is data readiness of the organization which basically includes
[00:05:52] the capability in data extraction, data storage, data privacy, data security
[00:05:59] and very importantly availability of sufficient and high quality training data which is
[00:06:03] actually needed for the AI models to work very effectively. The third is process readiness and
[00:06:09] you know considering that we are focusing around the customer services or CX processes
[00:06:14] in order to take full advantage of the gen AI on the CX processes the relevant CX processes
[00:06:21] actually needs to be reimagined and or re-engineered so that humans in AI can work
[00:06:27] together as co-pilots and deliver the business outcome for the clients
[00:06:31] and in addition there are regulatory and compliance issues that needs to be addressed in the future
[00:06:35] in the future process design and finally there is people readiness you know as we are you know
[00:06:41] developing and deploying gen AI based solutions organization basically requires skill sets across
[00:06:47] multiple types of skills and these includes design thinking skills to allow the re-imagination of
[00:06:53] the CX processes it includes the traditional AI ML and data science capabilities to curate the data
[00:07:03] before it is sent to an AI model and also very importantly software and hyper automation skills
[00:07:08] to develop and deploy gen AI enabled applications what we also found that in addition to these
[00:07:14] four you know you know top factors there are certain additional factors that are also very
[00:07:19] important which are driving the organizational readiness for deploying gen AI the first is you
[00:07:26] know the financial readiness you know do they have financial you know readiness to deploy such
[00:07:31] kind of solutions also this solution requires significant changes in the way the operating
[00:07:36] model work and process model works so what's been the traditional change management
[00:07:40] competencies of the organization and then finally if organization have past
[00:07:44] experience with transformative technologies they are better prepared to deal with these kind
[00:07:47] of challenges and you know what we what the survey found is that you know the factors
[00:07:54] vary across the industry segments but importantly you know technology and telecom industries were
[00:07:59] more ready for deploying gen AI solutions followed by BFSA healthcare and retail and one of the
[00:08:05] big standouts of that survey for me one of the big standout stats was that I think it was
[00:08:10] something like over 45 percent of enterprises are currently siding a shortage of internal
[00:08:16] technical expertise as a major barrier and I'm also reading outside of that survey that there's
[00:08:21] almost a big AI talent war out there with every business every start up desperately trying to
[00:08:26] hoover up all that AI talent to realize their ambition so how do you see companies overcoming
[00:08:33] that challenge to harness that full potential of generative AI because you need people to
[00:08:38] make that happen right you're right absolutely you know and you know uh you know as as
[00:08:43] you know I indicated earlier you know you know multi you know as you deploy you know and think through
[00:08:49] the gen AI you know solutions you know for an organization there are multiple types of capabilities
[00:08:54] and skills are required to reimagine design build deploy and then finally support gen AI
[00:09:00] applications right so for organizations you know who are lagging in their AI adoption readiness
[00:09:06] particularly in terms of technology and data that you talked about but also on process and
[00:09:10] people readiness a good strategy would be to seek out collaborative partnerships with third parties
[00:09:16] and then use those first parties to co-create the solutions and this actually if you know
[00:09:21] if organization follow this approach they can actually you know it can enable them to tap
[00:09:25] into external expertise on demand and then accelerate their gen AI adoption roadmaps
[00:09:31] and this is what actually WLS has done you know very successfully with many of our clients
[00:09:36] where we have had them to one identify what kind of business problem that they want to solve using
[00:09:42] gen AI and then we have worked very collaboratively with them and co-created uh you know the solutions
[00:09:48] where we have partnered with them you know either providing skills that they did not have
[00:09:53] or augmenting skills that they may already have a needed more of it
[00:09:56] when delivering multiple you know gen AI solutions with a very very clear focus on
[00:10:01] achieving measurable business benefits right and at this point of time you know in last you
[00:10:06] know 2018 months we have now either deployed or are developing about 90 use cases across the
[00:10:10] industry segments and multiple clients that you work with me and I think this year the
[00:10:15] transformative potential of gen AI's text generation capabilities has been widely recognized
[00:10:21] particularly in areas such as telecom and media tech and retail sectors but any business leader
[00:10:28] that is sat on the sidelines knowing what they need to do but just needs some examples of maybe
[00:10:34] bring those possibilities to life do you have any examples that you're able to share that would
[00:10:39] just bring those capabilities to life and help business leaders listening understand
[00:10:44] how they're being applied and will ultimately revolutionize their CXM operation um you're
[00:10:50] right me you know approximately 93 percent of the survey participants recognize the
[00:10:55] transformative potential of GenITV AI is you know text generation capability specifically
[00:11:01] in the CX operations while there are multiples of use cases but there may be four examples that I
[00:11:06] want to talk about the most common use case is to enhance customer service capabilities
[00:11:11] now providing instant and accurate and tailored responses to the queries
[00:11:16] the second is you know hyper personalization is also another example so many companies across
[00:11:21] industry segments are leveraging data and GenITV AI to deliver personalized and more relevant
[00:11:26] recommendations in real time as their agents service their clients cognitive and contextual
[00:11:33] summarization of large sets of unstructured data is another such use case which finds a
[00:11:38] significant adoption across industry segments and then finally supporting creation and access
[00:11:43] of knowledge management databases in other use case what GenITV AI can do it actually
[00:11:48] it can automatically summarize documents categorize information and even generate new content to keep
[00:11:55] knowledge basis fresh and relevant which then are used in the CX processes by the you know the
[00:12:01] companies and their you know uh employees servicing and clients to intelligently query
[00:12:08] or prompt and get very relevant and hyper personalized answers to deal with the you know customer
[00:12:13] situations that they may be solving and the survey also revealed varied AI adoption readiness
[00:12:21] across multiple industries and for me that that highlighted the differences in technology and
[00:12:25] data preparedness among so many other different factors and again for anybody listening
[00:12:31] are there any strategies that you would recommend for industries that might be
[00:12:35] lagging in readiness and currently playing catch up any strategies you'd recommend them
[00:12:40] yeah the survey basically you know indicated that you know there are you know variety of you
[00:12:47] know readiness you know across industry segments you know you know so what basically the survey
[00:12:53] found is that telecom and technology industries are actually leading in their genai adoption
[00:13:01] followed by BFSI health care and retail and if you look at the telecom technology and the
[00:13:07] media industry which sort of are leading this you know this sector by nature is extremely well
[00:13:13] equipped for embracing new technologies due to their existing technology frameworks you know
[00:13:18] their employees skill sets you know and their ongoing and continuous focus on customized and
[00:13:23] providing you know very customized and personalized services to their clients and these these
[00:13:29] you know sectors have always had prior experience of you know using transformative
[00:13:33] technologies right and that's the reason I think they are leading in that's what the survey indicated
[00:13:38] but I think the two key factors that other industry segments can learn from telecom technology
[00:13:43] and media sectors is one is their that change management maturity you know so they these
[00:13:51] organizations have been invested a lot in change management maturity and their technology
[00:13:56] readiness is also far superior including infrastructure and availability of high quality
[00:14:00] of data which is again and important prerequisite for deploying genia solutions
[00:14:06] completely agree with you the other thing we have to bring up whenever we mention AI
[00:14:11] things like regulatory compliance issues that also noted as significant challenges especially
[00:14:18] in the BFSI and health care sectors for example and there's also a lot of debates
[00:14:23] around the ethics and responsible AI as well so I know there's a lot of business leaders that
[00:14:29] this scares them a little bit I think in some ways that has prevented them from just diving
[00:14:33] straight in so how do you suggest that enterprises navigate those regulatory landscapes while also
[00:14:39] pursuing those gen AI innovations yeah so data privacy and regulatory compliance
[00:14:45] remain a prominent challenge in financial services and healthcare industries
[00:14:49] and hence the gen AI enabled processes in these industries will require a human centric
[00:14:54] approach now with humans and AI working together as co-pilots and allowing for a human oversight
[00:15:01] to ensure control compliance accuracy and effectiveness you know these industries
[00:15:07] one because of like regulatory nature of you know regulated nature of their business
[00:15:12] and two because of the complex nature of the the transactions you know
[00:15:19] you know it is appropriate for them to use a co-pilot approach instead of you know
[00:15:23] you know letting a you know AI based chatbot deal with that complexity right
[00:15:30] so these sectors also need to develop a comprehensive governance framework
[00:15:33] that covers you know the issues that you talked about like ethical privacy security legal
[00:15:39] regulatory obviously and also to some extent social issues right and some steps that
[00:15:44] you know can be taken to mitigate these issues can include you know things like controlling the
[00:15:49] type of data that is sent into an AI model implementing access controls on who has access
[00:15:56] to these AI models and then finally and very importantly implementing a continuous monitoring
[00:16:03] mechanism to evaluate the output and outcomes being delivered from GenRTVI and uses evaluations
[00:16:09] to further enhance the controls on the input content access and training of the GenRTVI models
[00:16:18] and if we were to zoom out given all of the surveys insights and everything you learned from
[00:16:23] them how does the WNS envision the future of gen AI enhancing business process management
[00:16:30] solutions and ultimately what role do you see WNS playing in this evolving ecosystem
[00:16:36] you know so as we discussed earlier nearly you know many of the organizations that don't have
[00:16:43] internal capabilities to deploy the solutions and we are an active partner helping many of our
[00:16:48] clients deliver you know this gen AI solutions but you know we at WNS believe in democratizing
[00:16:56] the use of gen AI and also very importantly democratizing the use of gen AI within
[00:17:01] the constraints of data privacy and security because that's a prime you know a mover right
[00:17:06] so with this as an operating philosophy we have adopted a three-pronged approach to support the
[00:17:11] evolving ecosystems in the in the business process management field that we work in
[00:17:15] the client base that we work with the first is capability build focused on skills required
[00:17:21] in our workforce design build deploy and support gen AI enabled solutions and as I mentioned
[00:17:27] earlier these skills include AI ML and data scientist software and hyper-probation skills
[00:17:33] cloud infrastructure capabilities security and privacy expertise right the second is
[00:17:40] solutions build so you know once we have the capability then we have to build solutions
[00:17:44] and the focus is on reimagining our clients business processes and then co-creating new
[00:17:50] solutions and services with them that will allow our clients to utilize the full power of gen AI
[00:17:55] with humans in the AI working as co-violates and the third is a market positioning
[00:18:03] to create an integrated go-to-market strategy combining gen AI with other digital technologies
[00:18:09] to maximize business value proposition that would be exciting times ahead and of course in those
[00:18:14] months ahead I think we can all safely predict enterprises will continue to explore gen AI for
[00:18:20] a variety of use cases but as someone that's right in the heart of this space armed with
[00:18:25] that future mindset and listening to so many business leaders around the world are there any
[00:18:31] or are there any other long-term impacts that you anticipate on customer experiences and indeed
[00:18:36] operational efficiencies and again any advice on how companies should maybe be preparing for
[00:18:42] these changes right now so gen ed AI has the potential to revolutionize the cx operations by
[00:18:49] addressing three dimensions of efficiency effectiveness and customer impact now these technologies
[00:18:56] you know enhance operational efficiencies they also improve productivity of the workforce
[00:19:03] and which actually leads to a significant cost reduction so that's a you know a gain and benefit
[00:19:09] that organizations will realize is the deployed gen AI solution the second as I said effectiveness
[00:19:14] you know gen AI also allows the workforce to be very effective because it allows them to analyze the
[00:19:20] customer data to hyper personalize interactions and provide more relevant recommendations this
[00:19:26] delivering customers impact significant customer impact in terms of improved customer satisfaction
[00:19:32] improved npsa's or other customer measures that the that the organization may have
[00:19:37] so enterprise you know who'd really want to adopt gen AI must plan for an address a
[00:19:43] variety of challenges across technology data people processes and very importantly change
[00:19:49] management and they must also ensure that the gen AI applications that they are building basically
[00:19:57] take this five checkboxes and these are that the applications must be unbiased and accurate
[00:20:03] they must be safe and secure they must be honest and appropriately trained
[00:20:08] they must be empowering and democratize and finally sustainable one of the things that attracted
[00:20:13] me to you guys is that wns has got this reputation for combining industry knowledge with technology
[00:20:20] with analytics and process expertise to help co-create innovative digitally led transformational
[00:20:26] solutions around the world but before I let you go I'd love to dig a little bit deeper
[00:20:31] on your personal story and find out how you've been able to play such a huge part in this
[00:20:37] and of course if we any of us look back at our career none of us are able to achieve
[00:20:42] any degree of success without maybe a little help along the way so I'm curious
[00:20:47] has there been a particular company institute or something that you're grateful towards which
[00:20:52] maybe helps you get where you are and helped you play that role that you play to be honest
[00:20:58] yeah really you know obviously you know in a long career that I've had you know there
[00:21:01] were multiple people who influenced me who helped me but I think what I want to talk about is the
[00:21:07] exposure and experience I got in the first company that I worked for it was a company called CMC
[00:21:13] it doesn't exist in the current in the inner shape and form today because it was a good
[00:21:16] got acquired by a tier one system integrator that company you know bread entrepreneurs you know we
[00:21:24] were taught in that company that no idea is a bad idea and we are only limited in our
[00:21:30] understanding of the use of that idea at that point of time right so you know and that's
[00:21:35] been operating philosophy that I have had in my you know in my career you know curiosity never
[00:21:40] killed the cat in that form we were always encouraged to innovate and it was okay to fail
[00:21:45] you know as long as we were learning from those failures and again you know I can go on and on
[00:21:50] about the learning you know the eight years that I spent in that company but I owe a lot to
[00:21:55] you know career that I've had you know after I left the company as an entrepreneur you know
[00:21:59] for few years and then obviously what I've been doing at WNS for many years now
[00:22:03] it's so important to hear stories like that and how they shape us all as individuals and
[00:22:09] the work we're doing now and both in the future and for anyone listening that wants to find out
[00:22:14] more information maybe explore the report that we've referenced today or just find out more
[00:22:18] about yourself your team at WNS the work that you're doing is there anywhere in particular
[00:22:23] you'd like to point everyone listening yes yes absolutely you know so there's a lot of you
[00:22:28] know articles white papers knowledge you know we are available on WNS.com which is our website
[00:22:35] now you can also refer to our social media handles around on Facebook Twitter LinkedIn and
[00:22:40] Instagram and then obviously you know I'm I'm on LinkedIn fairly active on LinkedIn so you
[00:22:45] know you know audience can actually look at my LinkedIn profile you know and if they need
[00:22:49] to connect with me you know it's you know that's that's the place to connect with me and happy to
[00:22:54] answer questions WNS is a very active you know technology digital genai you know
[00:23:01] the portfolio and we publish a lot on the social media so you'll be you know audience will be able
[00:23:06] to find a lot of content on some of these handles that I talked about. Fantastic well I
[00:23:11] would add links to all those things including a link to that every groups generative AI in
[00:23:17] CXM survey report that's supported by WNS I'll put a link there so much I love talking with you
[00:23:23] about today in particular digging deep on that survey that highlighted some of those
[00:23:28] greatest barriers to success for genai adoption but most importantly that willingness to adopt
[00:23:33] the technology for so many different use cases so more than anything I would just a big thank you
[00:23:38] for taking the time to sit down with me and share some of those stories I really hope that they
[00:23:43] have helped some business leaders listening around the world but thank you Sanjay.
[00:23:47] Thank you Neil the pleasure of all mine you know you had very thought-provoking questions
[00:23:51] and you know it was a pleasure to answer them hopefully I did a good justice to be able to
[00:23:56] answer those questions but thank you for your for for this opportunity. Wow what an incredible
[00:24:02] goal and after our conversation I'm left with a profound understanding of the landscape of
[00:24:07] GenaVtv AI readiness amongst enterprises I've heard so many stories over the last 18 months
[00:24:13] somewhere in denial for a certain amount of time others were very very nervous about
[00:24:18] what happens to company data in machine learning language models and many were concerned about
[00:24:23] regulation and you just sat on the sidelines but I think that has gone now and the insights from
[00:24:29] the WNS and every group survey they illuminate a path forward they highlight the critical elements
[00:24:36] of technology data process and how people will dictate the pace of success of generative AI
[00:24:44] integration it's not AI taking over it's people and AI collaborating with one another not competing
[00:24:52] and also I think Sanjay's expert analysis underscores that importance of strategic
[00:24:57] partnerships ethical consideration a human-centric approach to navigating some of the challenges
[00:25:03] and those fantastic opportunities that lie ahead but as industries continue to evolve and adapt
[00:25:10] to this technological renaissance of sorts I think it's clear that gen AI will play a central role
[00:25:16] in transforming customer experiences and operational models alike but of course the bigger question is
[00:25:23] what step will you and your organization tech to harness the potential of generative AI how are
[00:25:29] you going to navigate this journey ahead he is complex it's probably something you can't do on
[00:25:34] your own you're going to need a little help you're going to need those strategic partnerships
[00:25:37] but please I invite you to share your thoughts join this conversation I want us all to explore
[00:25:42] the limitless possibilities of this AI driven future I think we can all accept it's not going
[00:25:47] anywhere now none of us have got the answers on our own but together if we could pull our resources
[00:25:52] put all of our ideas concerns and everything in between put them in a big melting pot man we
[00:25:58] could learn so much from each other so as always email me tech blog writer outlook.com twitter
[00:26:04] LinkedIn instagram at neil c us let's keep this conversation going and I've got another great guest
[00:26:11] lined up tomorrow I feel very fortunate at the moment to have had so many great guests and
[00:26:16] we've had people from Microsoft from Intel BAE KPMG couch base Twilio they're just a few that I've
[00:26:24] been speaking to this week and if you'd like to come on the podcast please let me know we do
[00:26:27] have a bit of a backlog of about six weeks to get on the show but if you'd like to join me
[00:26:32] let me know but that's it for today so thank you for listening as always and until next time don't be a stranger