GenAI Without Governance is a Disaster Waiting to Happen

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“Regulation is the biggest challenge with large-scale adoption of genAI in enterprises. Lack of talent and agile approach to keep up with the latest/greatest innovations across various open and closed source models is the challenge. Clients often cite ethical AI development as a big responsibility,” says Jay Dalvi, Enterprise Sales Director at Haptik.

With a successful 10-year career in martech, Jay has built substantial revenue growth across technology, banking, telco, healthcare, and the public sector. Known for his expertise in go-to-market strategy development and outbound sales among others, Jay has a proven track record of scaling businesses from $0 to $50 million ARR in fast-paced, high-growth environments.

Currently leading sales for Haptik‘s genAI-powered Conversational Commerce stack for Enterprises, we asked Jay about his thoughts on genAI and how Haptik is embracing the rapidly advancing technology. 

Excerpts from the interview

What excites you, and what scares you about genAI? 

What’s scary is that I don’t think we’re just augmenting humans; we’re creating our part replacements. I’m excited that genAI can achieve 10x productivity with a short learning curve to be able to achieve that but it isn’t a magic bullet. It’s a powerful tool that requires strategic implementation, human oversight and prompt engineering prowess – you’ll be surprised how many people are bad at giving basic prompts. If we keep doing this without proper governance structures – on an organisation or government level – it’s a disaster waiting to happen.

How do you see genAI transforming the marketing function? What are the top three use cases?

Traditional marketing roles will disappear. The survivors will be AI conductors, not traditional marketers.

1. Hyper-personalisation at scale: Every customer gets a unique experience. Marketing to a segment of one is truly here.
2. AI agents for every marketing task: Agents won’t just assist; they’ll autonomously execute complex strategies, learn from outcomes, and continuously optimise performance. Marketers should learn to orchestrate this symphony of agents
3. Conversational marketing: As user behaviour shifts from search to prompts, marketing will become a dialogue. AI-driven conversational interfaces will engage customers in real-time, personalised interactions. 

Tell us about Haptik’s suite of genAI products and future plans for the ME industry.

With feedback from customers, Haptik’s genAI suite will continue to evolve keeping regional nuances and data residency requirements. We’ve noticed that WhatsApp as a channel is being underutilised and we’ll evangelise how genAI-powered WhatsApp alone can 10x your returns vs. just WA marketing. We’re also picking up proprietary projects using genAIs multimodal capabilities in image, video and voice.

How scalable are these tools in handling large volumes of content generation?

Scalability isn’t just a feature; it’s a necessity. If your genAI platform can’t handle exponential growth, it’s already outdated. Being a Jio company, we’re battle-tested to 100 million users scale which I don’t think anyone else has had the privilege of, especially so early on in their GenAI journey.

DOWNLOAD PLAYBOOK: The Potential of Generative AI in the BFSI Industry 

What should a brand leader’s criteria be when investing in genAI solutions for marketing?

The real criterion is appetite for risk vs. reward. GenAI is fast evolving, and it’s easy to be left behind if you don’t invest now. There is no real middle ground when it comes to genAI investments.

Key criteria:

1. Realistic expectations (possible vs. really possible today)
2. Data and prompt engineering talent 
3. Ability to work at 90% accuracy 
4. Willingness to test in the real world
5. Time

What long-term trends or challenges do you foresee, and how is Haptik preparing to address them?

Regulation is the biggest challenge with the large-scale adoption of genAI in enterprises. Lack of talent and agile approach to keep up with the latest/greatest innovations across various open and close source models is the challenge. Clients often also cite ethical AI development as a big responsibility. We’re working closely with our prospects and customers to keep them up to date on our roadmap, participating in public forums to improve regulatory oversight and abiding by our own ethical use of AI policy at Haptik.