How Conversational AI Is Supercharging Business Productivity—And How To Get Started

Gaurav Tewari, Founder and Managing Partner of Omega Venture Partners

Recent advances in artificial intelligence (AI) have catalyzed a sea change in the ability of computers to engage in live, human-like conversation with people. Today we are seeing conversational AI systems with unprecedented sophistication in their ability to converse in a manner that is practically indistinguishable from speaking with a human. Going far beyond Alexa or Siri responding to a simple query, today’s state-of-the-art conversational AI (CAI) systems navigate complex dialogue, understand nuanced intent, navigate multi-topic, multi-turn conversations and articulate cogent, on-point responses. The rise of CAI is creating a new paradigm for customer experience, personalization and productivity in the modern workplace. As a venture capital investor who focuses on AI and business software, I have been privy to the breakthroughs in CAI and invested in industry-leading companies.

Back in the 1960s, researchers at MIT pioneered ELIZA, an early natural language software, that attempted to simulate human dialogue. However, ELIZA and programs like it were severely limited in their real-world applicability. These systems were programmed with brittle rules and canned responses and could only handle a very narrow set of use cases without breaking down.

By contrast, today’s CAI systems are powered by machine learning, giving them far greater dexterity as well as the ability to self-improve over time. The revolution in CAI has benefitted from an abundance of data as well as the continuously improving price-performance of compute—both necessary ingredients to train good AI systems. And, crucially, recent years have seen extraordinary funding and talent funneled toward developing groundbreaking large language models, which provide a core foundation for the development of conversational AI applications.

Use Cases For CAI

I believe business is poised to undergo a significant transformation as a result of AI. Below are three compelling CAI use cases that businesses can harness today.

1. Customer Service

No one likes waiting on hold to reach a customer service agent, and navigating an endless phone tree is no fun. The rise of CAI means that large chunks of front-line customer service can now be automated. AI can handle most high-volume, routine queries. When a more nuanced or emotional situation arises, CAI systems are smart enough to escalate to a human agent, while equipping the agent with rich context such as the caller’s identity, relationship history, applicable company policies and learnings from other similar customer enquiries.

We are already witnessing the beginnings of this future, and I’ve noticed the companies that adopt these solutions are seeing substantial savings and higher customer satisfaction ratings.

2. Sales

Sales processes often require collecting data from prospective customers, both to qualify the customer as well as to curate the appropriate offering. The process can be dull, time-consuming and error-prone. CAI changes the game by enabling such information to be collected automatically and interactively from a prospective customer, and they can do so 24/7. These systems can also tie together information from multiple touchpoints and channels (e.g., chat, text, phone, web) to mitigate redundancy and error, while reducing customer friction.

Automating customer qualification and data collection in this manner provides value for both the customer and the business. From a customer’s perspective, the value of a streamlined, self-serve conversational interface that retains context and memory across interactions and helps navigate a process is hard to overstate. For the sales rep, such solutions reduce the tedium of data collection and data entry, often across disparate systems. Sales reps can now spend their time where it matters most—in building meaningful relationships as well as in customer interactions that require a human touch.

3. Cybersecurity

While the notion of using a person’s voice to verify their identity has been around for a while, CAI takes voice biometrics to the next level. Instead of a pre-formulated phrase or sentence, CAI systems can capture much higher resolution data associated with a person’s vocal characteristics—for example, tone, speed, word choice, sentence structure, grammar, accent, inflections, mannerisms—and tie these with identifiers such as location, time, day, weather, prior interaction history and real-time knowledge of threats.

A biometric voice system can improve employee and customer satisfaction by providing both efficient and robust identification. Users appreciate not having to fumble for their ID cards or remembering answers to security questions. Organizations benefit from decreased fraud and improved usability. In sectors such as healthcare and financial services, where confidentiality is important, voice biometrics can also serve to limit unnecessary dissemination of private information.

Best Practices

Business leaders adopting CAI solutions should prioritize defining clear use cases and integration into existing systems. A well-defined business use case, with quantifiable success metrics, is critical to managing the scope of the deployment and measuring return on investment. It is also imperative to ensure that the CAI is well-integrated with existing workflows and that it can access the data it needs to fulfill its use case.

Lastly, CAI systems are not a panacea. Despite the fact that CAI systems continually advance, the real world presents many novel situations that require improvisation, flexibility and exception handling. A CAI system cannot anticipate or prepare for every scenario that might arise. When nuance and judgment are required, businesses should provide human oversight and failover. By reducing repetitive tasks, CAI empowers people to spend more of their time engaging in strategic initiatives that require creativity, insight, intuition and common sense.

As AI continues to permeate every economic sector, I believe we will see more practical applications that unlock tangible and substantive value. CAI is one such application that has reached an inflection point. With continued advancement, I look forward to the additional novel use cases poised to be unleashed in the years ahead.


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