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sierra ceo bret taylor on why the In a recent conversation, Bret Taylor, CEO of AI startup Sierra and chairman of OpenAI, shared insights on the evolving landscape of artificial intelligence and its parallels to the dotcom boom.

sierra ceo bret taylor on why the

Background on Bret Taylor

Bret Taylor has a storied career in the tech industry, having been an early engineer at Google before co-founding FriendFeed, a social network that was sold to Facebook in 2009. At Facebook, he served as Chief Technology Officer. He later founded Quip, which Salesforce acquired, leading to his eventual role as co-CEO of Salesforce. Taylor’s extensive experience also includes leading Twitter’s board during Elon Musk’s acquisition and becoming chairman of the OpenAI board following the controversial firing and rehiring of CEO Sam Altman. His deep understanding of technology and business positions him uniquely to comment on the current AI landscape.

The Birth of Sierra

In early 2023, shortly after announcing his departure from Salesforce, Taylor found himself captivated by the release of ChatGPT. He described this moment as a “cosmic” convergence of events that ignited his passion for AI. “I was trying to leave and then figure it out,” he recounted, reflecting on how he became obsessed with the technology. His conversations with industry peers, including LinkedIn co-founder Reid Hoffman, further fueled his enthusiasm for AI, particularly large language models.

Recognizing the transformative potential of AI, Taylor and his long-time friend Clay Bavor decided to establish Sierra. Their goal was to create AI agents that could revolutionize customer support. Taylor likened this moment to the dawn of the internet, where a seismic shift in technology opened up numerous business opportunities. “When you have a seismic shift in technology, a lot of business opportunities present themselves,” he explained, drawing parallels to how the internet disrupted established companies and birthed giants like Amazon and Google.

Understanding Sierra’s Unique Approach

Sierra’s business model is distinct from traditional software companies. Instead of charging clients upfront fees, Sierra operates on an outcome-based pricing model. “We charge only for outcomes,” Taylor stated. This means that clients pay only when the AI agent successfully resolves a customer inquiry, while transfers to human agents incur no cost. This model aligns the interests of Sierra with those of its clients, fostering a partnership built on accountability.

Transforming Customer Support

Customer support is not a new concept, but Sierra’s approach is innovative. Taylor emphasized that the relationship between software vendors and companies must evolve in an outcome-based pricing environment. Traditional software implementations often lead to blame-shifting among vendors and clients, creating a lack of accountability. In contrast, Sierra’s model encourages a collaborative partnership focused on achieving measurable results.

To facilitate this, Sierra emphasizes product usability, allowing both technical and non-technical users to build AI agents. “We’re trying to empower as many customer experience professionals as possible,” Taylor noted. Additionally, Sierra provides extensive support for agent development, ensuring that clients can successfully deploy their AI agents.

Targeting Large Enterprises

Sierra has strategically chosen to focus on large enterprises, with 50% of its clients generating over $1 billion in revenue annually. Taylor explained that large companies face significant challenges in customer engagement, particularly when it comes to cost-per-contact metrics. “If you are a large consumer brand and you have 100 million consumers around the globe, you could not have had a conversation with all of them,” he said.

Before the advent of large language models, the cost of engaging with customers via phone or chat often exceeded the revenue generated from those interactions. Taylor pointed out that this economic barrier has historically limited customer support options for many brands. However, with the introduction of AI, the cost of customer interactions has dramatically decreased, enabling companies to engage with customers at scale.

Enhancing Customer Experience

With the ability to conduct significantly more conversations at a lower cost, companies can now focus on improving customer retention and satisfaction. Taylor highlighted that many organizations are beginning to view AI not just as a cost-saving measure but as a strategic tool for gaining market share. “If you can improve customer attention by 100 basis points, that’s a lot of value,” he remarked, emphasizing the potential for AI to transform customer experience.

Real-World Applications of AI Agents

When asked about the capabilities of Sierra’s AI agents, Taylor provided several compelling examples. For instance, some retailers utilize AI agents to process warranty claims by allowing customers to submit photos of damaged goods. The AI can then adjudicate the claim and connect to inventory systems to ship replacements without any human involvement. “These agents are remarkable at what they’re doing,” he stated, underscoring the efficiency and effectiveness of AI in handling complex tasks.

Another example involves AI agents facilitating home refinancing processes end-to-end, again without human intervention. Taylor noted that while many companies are still exploring the potential of AI, Sierra’s clients are already leveraging these capabilities to streamline operations and enhance customer experiences.

Challenges and Innovations in AI

Despite the impressive capabilities of AI agents, Taylor acknowledged that challenges remain, particularly in regulated industries such as healthcare and finance. He discussed the importance of implementing effective guardrails to ensure compliance and accuracy in AI-driven conversations. “How do you put AI-based guardrails around it?” he posed, highlighting the complexities involved in deploying AI in sensitive environments.

For instance, transcription accuracy becomes critical when dealing with sensitive information like account numbers. Taylor explained that Sierra’s platform is designed to address these challenges, incorporating multilingual capabilities and advanced AI models to enhance performance. “Our platform is really designed to solve those problems,” he asserted, emphasizing the company’s commitment to delivering reliable AI solutions.

The Future of Voice in AI

As the conversation progressed, Taylor expressed his belief that voice interactions will play a significant role in the future of AI agents. He noted that voice is already a larger component of Sierra’s platform than text, which is remarkable given that the voice feature was only launched in November of the previous year. “Voice is the most ergonomic interface,” he stated, highlighting its accessibility and ease of use.

With advancements in voice recognition technology, Taylor envisions a future where voice interactions become the primary mode of communication with AI agents. This shift could democratize access to technology, particularly for individuals who may struggle with traditional text-based interfaces. “If most of the ways you interact with digital technology is just speaking, what a great way to make it accessible to everyone,” he remarked.

Conclusion: The AI Bubble and Its Implications

As Taylor reflected on the current state of the AI industry, he drew parallels to the dotcom boom, suggesting that we may be experiencing a similar bubble. The rapid advancements in AI technology, coupled with significant investments and public interest, have led to a surge in startups and innovations. However, Taylor cautioned that, like the dotcom era, not all companies will survive the inevitable market corrections.

Nonetheless, Taylor remains optimistic about the future of AI and its potential to reshape industries. “I think it’s a really exciting time to be in this space,” he concluded, emphasizing the transformative power of AI in customer experience and beyond.

Source: Original report