Wintage Club Insights

Human touch in AI: The future of enterprise technology

Highlights from our conversation with Vinod Muthukrishnan, Chief Customer Officer at Uniphore

Shrivarshini Somasekhar

Last Updated:

March 26, 2026

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AI Summary

The future of enterprise AI is not full automation — it is human-AI collaboration where AI handles data synthesis and repetitive work while humans provide judgment, empathy, and strategy.
Enterprise buyers trust AI outputs only when they can verify them — source attribution, audit trails, and human review loops are essential for adoption.
The best enterprise AI tools feel like assistants, not replacements — they augment human capabilities rather than attempting to bypass human decision-making.
SiftHub embodies this philosophy: AI generates answers and content with full source attribution, but humans review, customize, and decide what goes to the buyer.
Organizations that get the human-AI balance right will outperform both fully manual teams (too slow) and fully automated teams (too impersonal) in enterprise sales.

The future of enterprise AI is not full automation — it is human-AI collaboration where AI handles data synthesis and repetitive work while humans provide judgment, empathy, and strategy.
Enterprise buyers trust AI outputs only when they can verify them — source attribution, audit trails, and human review loops are essential for adoption.
The best enterprise AI tools feel like assistants, not replacements — they augment human capabilities rather than attempting to bypass human decision-making.
SiftHub embodies this philosophy: AI generates answers and content with full source attribution, but humans review, customize, and decide what goes to the buyer.
Organizations that get the human-AI balance right will outperform both fully manual teams (too slow) and fully automated teams (too impersonal) in enterprise sales.

We were thrilled to catch up with Vinod Muthukrishnan as part of our flagship interview series, "Wintage Club Conversations" last month. Vinod has had a uniquely diverse career journey, starting at the Merchant Navy, transitioning into a strategy and global sales role in a Fintech startup, before going on to becoming a co-founder and CEO of CloudCherry which was acquired by Cisco in 2019. Today, Vinod leads all things customer experience at Uniphore, one of the largest B2B AI-native organizations.

When asked about his learnings from his journey so far, Vinod said, "I've learned that a small group of highly motivated, skilled, and mission-oriented people can do anything."

This blog delves into the insights shared by Vinod, shedding light on the pivotal moments and strategies that have shaped the enterprise tech landscape. You can watch the full interview here.

The mass commercialization of enterprise tech

Vinod recalls a time not so long back when, if you said you worked in 'enterprise tech', no one knew or cared about what you did. Today for the first time, thanks to ChatGPT, your parents, children, neighbors, friends, and most importantly your customers have all experienced the power of what AI can do. Vinod calls this the 'mass commercialization of enterprise technology’; this has been incredibly emancipating for Uniphore.

Earlier, individual buyers would come in to buy an enterprise AI product without the budget backing, and there would be a need to sell the purchase internally. Now, boardroom conversations are around how an organization needs to be using AI. Large enterprises are also no longer looking for an AI 'product' but rather for AI strategy partners and platforms. Vinod says this has been a tectonic shift.

3 attributes enterprise AI tech buyers value

When discussing this shift in attitude towards enterprise AI tech, Vinod outlined three key attributes that buyers look for in an enterprise technology vendor:

Being AI-native: Buyers care about whether your organization has worked foundationally with AI over the years, or if you're just looking to ride the latest tech wave.
Platform over products: AI is still evolving so your buyer's needs are not determinate. They're looking for a platform that will continue to evolve with them and match their needs at every stage.
Strategic AI partner: While everyone is looking to implement AI to boost productivity and efficiency, organizations don't always have a clear idea of what that looks like for their company or their industry. They're looking for more than just a vendor,

AI is core to Uniphore's strategy

Internally, Uniphore has embraced AI as not just a tool but a core component of its strategy. Vinod shared that over the last several months his organization has automated processes, enhanced efficiency, and accelerated its operations. He said, "You can't be an AI-native company working in AI for 16 years, spreading the AI gospel, and then not using it internally." Uniphore embodies the true essence of an AI-native company.

Making digital interactions more human in 2024

Looking ahead, Uniphore has set ambitious goals for 2024, focusing on aggressive top-line growth, net retention, and account expansion. The company views its relationship with clients not as transactional but as a partnership, aiming to drive mutual success. A key part of this strategy is hiring the right people who fit into the company's culture, underscoring the belief that the future of enterprise AI is human.

Vinod shares that Uniphore's vision for the future is clear: to make digital interactions more human. The company believes that technology should enhance efficiency and predictability while making processes more human-centric. This vision is not just about improving customer interactions but about redefining the role of AI in enterprise technology.

Check out the full video for an in-depth conversation with Vinod? You can watch it below.

What does 'human touch' mean in the context of AI-powered enterprise technology?

Human touch in AI enterprise technology refers to the elements of interaction, judgment, and relationship context that require human involvement to create genuine value—as distinct from the information work that AI handles effectively. In sales, human touch manifests as: genuine empathy with buyer challenges, judgment about when to push versus when to listen, the ability to read room dynamics in a live deal, and the trust that comes from a buyer knowing they're working with someone who personally cares about their success.

How does AI threaten—or strengthen—the human element in enterprise sales?

Used well, AI strengthens the human element by removing the administrative overhead that was consuming the time and energy that should go into relationship building. When an SE doesn't spend an evening assembling an RFP response, they're fresher and more engaged in the next morning's buyer conversation. When a rep doesn't spend an afternoon creating collateral, they have more time to understand the buyer's political landscape. AI that handles information work returns capacity to human work—but only when adopted with that intention explicitly in mind.

Why do enterprise buyers still value human relationships despite AI capabilities?

Enterprise buyers value human relationships because significant software investments involve risk, trust, and change management that purely transactional interactions can't navigate. Buyers need confidence that someone at the vendor organization understands their specific situation and cares about their success—not just closing the deal. AI can inform the conversation, but the human connection that converts an evaluation into a partnership and a partnership into a long-term customer requires human judgment, empathy, and consistent relationship investment.

How should companies communicate their use of AI to enterprise customers?

Transparency is the right standard: customers don't object to AI being used to prepare better materials or respond faster; they object to AI being used without awareness in ways that create inaccuracy or reduce the care in communication. Being clear that your team uses AI assistance to prepare more accurately and respond faster—while ensuring human review and ownership of all buyer communications—is a credibility-building posture, not a damaging admission. Most enterprise buyers use AI in their own operations and understand its appropriate role.

What is the risk of over-automating human touchpoints in enterprise sales?

Over-automation creates a recognizable hollowness: emails that are clearly AI-generated without personalization, follow-ups that don't reference the actual conversation, and responses that are technically accurate but emotionally disconnected. Enterprise buyers—particularly at senior levels—are highly attuned to these signals. The risk is not just a lost deal; it's the relationship damage that comes from the buyer feeling they're engaging with a process rather than a team. Human touchpoints must be protected deliberately as AI handles more of the surrounding workflow.

How does SiftHub balance automation with preserving human value in sales?

SiftHub is explicitly designed to augment rather than replace human sales professionals. The platform handles information retrieval, first-draft generation, and content assembly—tasks that consume time without contributing relationship value. The output of every SiftHub workflow goes to a human for review, personalization, and final judgment before it reaches a buyer. This human-AI handoff is deliberate: AI handles scale and speed; humans handle the relationship, accuracy review, and the contextual judgment that determines whether to send, modify, or override what AI produces.

What will enterprise technology look like when human touch and AI are optimally integrated?

Optimal integration looks like: AEs and SEs who spend 80% of their time in genuine buyer engagement because AI has handled the surrounding information work; proposal and RFP teams that focus on strategy and differentiation because AI handles compliance checking and first-draft production; sales leaders who make decisions based on comprehensive deal intelligence rather than weekly forecast calls with incomplete information. The human element is elevated, not diminished—doing more strategic work with higher impact because AI has cleared the administrative noise.

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