Strategic Partnerships: Expanding Market Reach
In the dynamic landscape of GenAI, Perplexity AI distinguishes itself by targeting the specific needs of business users. Although it lacks the broad consumer recognition of OpenAI or Google, Perplexity AI is achieving substantial progress through strategic alliances and a distinctive approach to AI functionality.
Perplexity AI has been actively cultivating alliances with major players across various sectors. These collaborations are crucial for broadening its market footprint and incorporating its AI capabilities into diverse ecosystems.
Samsung: Perplexity AI is reportedly in advanced discussions with Samsung to integrate its AI functionalities into Samsung’s smartphone ecosystem. This potential integration could lead to Perplexity’s AI replacing Google’s Gemini assistant on Galaxy devices. The plans involve incorporating Perplexity AI into Samsung’s web browser and the Bixby assistant, thereby improving the overall user experience.
Motorola: A collaboration with Motorola aims to integrate Perplexity’s AI technology into Motorola smartphones. The objective is to enhance user experience through AI-driven features, providing users with more intuitive and efficient interactions with their devices.
PayPal: By integrating PayPal as a checkout option within its chatbot, Perplexity AI is simplifying transactions and offering users a seamless purchasing experience. This integration enhances convenience and positions Perplexity AI as a versatile tool for both information retrieval and practical applications.
SoftBank: Further strengthening its ties with investor SoftBank, Perplexity AI has expanded its strategic partnership. SoftBank’s sales force will now promote Perplexity’s Enterprise Pro plan to corporate clients in Japan. This partnership leverages SoftBank’s extensive network and market presence to accelerate the adoption of Perplexity AI in the Japanese enterprise sector.
Wiley: By partnering with Wiley, Perplexity AI provides users with direct access to Wiley’s extensive content library through its chatbot. This collaboration enhances the chatbot’s capabilities by providing a wealth of information and resources, making it an invaluable tool for research and learning.
Enterprise Investment in AI: The Growing Trend
Data from PYMNTS Intelligence indicates that businesses are increasingly investing in AI technologies. A substantial 90% of CFOs reported witnessing “very positive” ROI in December 2024, a significant increase from the number of respondents who reported the same sentiment nine months prior. This data highlights the growing recognition of AI’s potential to drive productivity and efficiency within organizations. Rather than entirely replacing human workers, businesses are now focusing on leveraging GenAI to augment and enhance their existing workforce.
Strategic Positioning: Beyond Brand Recognition
Perplexity AI’s cultivated strategic alliances have positioned the startup for significant growth, irrespective of its lower brand recognition compared to industry giants like OpenAI or Google. While figures like Sam Altman, CEO of OpenAI, and the established brands of Google and Microsoft often dominate headlines, Perplexity AI is quietly advancing by addressing specific enterprise needs. Despite being excluded from White House AI summits under both the Biden and Trump administrations, Perplexity AI CEO Aravind Srinivas has focused on building a product that resonates with business requirements.
The Enterprise Appeal: Why Businesses Choose Perplexity
Enterprises are attracted to Perplexity AI for several compelling reasons, primarily its flexible and user-centric approach.
Dev Nag, founder and CEO of QueryPal, a former Google and PayPal employee, emphasizes that “Perplexity has shown that being a model ‘polyglot’ can create more strategic advantages than owning the best single model.” Unlike competitors like ChatGPT that rely primarily on their own large language models (LLMs), Perplexity AI can seamlessly switch between various LLMs, including ChatGPT, Claude, and its own Sonar model. This adaptability ensures that users receive the most appropriate and effective responses based on their specific needs.
User-Centric Model Aggregation
Perplexity AI’s approach is fundamentally user-focused. It prioritizes delivering the best possible results by aggregating multiple LLMs and allowing users to access a range of options. Nag explains, “While everyone fixates on who builds the smartest AI, Perplexity discovered that aggregating multiple LLMs and letting users hop between GPT-4, Claude 3.5, and their own Sonar model delivers better economics and resilience.”
For instance, if OpenAI increases API prices or experiences an outage, Perplexity AI can seamlessly reroute traffic to an alternative LLM, ensuring uninterrupted service and cost-effectiveness. This flexibility is a significant advantage for enterprises that rely on consistent and reliable AI solutions.
Scalability and Cost Efficiency
Perplexity AI’s infrastructure enables it to handle a substantial volume of queries without incurring prohibitive costs. According to Nag, “This approach lets a 150-person startup handle 400 million queries monthly without the crushing compute costs that would bankrupt most teams trying to run frontier models end-to-end.” This scalability and cost efficiency make Perplexity AI an attractive option for businesses looking to implement AI solutions without straining their resources.
Enterprise Partnerships: Technical Flexibility and Transparency
A key factor driving Perplexity AI’s enterprise partnerships is its technical flexibility, combined with a focus on transparency and auditability. Nag notes, “The enterprise partnerships stem from this technical flexibility combined with something OpenAI initially missed: Citations and transparency actually matter more to institutional buyers than raw but untraceable intelligence.”
Perplexity AI’s emphasis on providing citations and verifiable information aligns with the stringent requirements of enterprise clients who need reliable and trustworthy data. This provides a layer of accountability that many businesses require for compliance and risk management purposes. The ability to trace the source of information ensures that decisions made based on AI-driven insights are well-informed and justifiable.
Understanding Business Needs: A Key Differentiator
Perplexity AI’s success in the enterprise sector is rooted in its deep understanding of business needs. “Perplexity’s enterprise savvy comes from understanding that B2B adoption follows completely different rules than consumer viral growth,” Nag points out.
While ChatGPT gained widespread popularity through its capabilities and user-friendly interface, enterprises have different priorities. “While ChatGPT conquered hearts and minds through pure capability, enterprises needed the boring stuff first: SOC-2 compliance, data residency guarantees, and audit trails,” Nag adds. Perplexity AI recognized these fundamental requirements early on and built its offerings to meet these specific needs. These seemingly mundane but crucial aspects of enterprise-grade AI solutions set Perplexity AI apart from more consumer-focused offerings. By prioritizing security, compliance, and accountability, Perplexity AI has positioned itself as a trusted partner for businesses seeking to leverage AI in a responsible and reliable manner.
Competing, Not Toppling: A Unique Market Position
Darren Kimura, president and CEO of AI Squared, explains that Perplexity AI and OpenAI’s ChatGPT represent distinct approaches within the AI landscape. He states, “Perplexity positions itself as a real-time answer engine to provide concise, cited responses. This emphasis on provenance can appeal to users who are seeking verifiable information, such as researchers and executives.”
In contrast, ChatGPT is designed as a general-purpose AI assistant, excelling in creative tasks, long-form reasoning, and brainstorming. Kimura notes that ChatGPT’s strength lies in its contextual understanding and retention capabilities. These different approaches appeal to different segments of the market. Where Perplexity emphasizes accuracy and verification, ChatGPT focuses on versatility and creative application.
Market Presence: Volume vs. Value
Despite its strategic positioning, Perplexity AI is still considerably smaller than OpenAI in terms of market presence. Data from Semrush indicates that ChatGPT recorded 4.5 billion web visits in April 2025, while Perplexity AI had 125.4 million visits. DeepSeek and Google’s Gemini followed with 419 million and 133 million visits, respectively.
However, Perplexity AI’s strategy is not centered on dominating the market in terms of sheer volume. It aims to capture a niche as a research-focused alternative to general-purpose assistants, with a business model predicated on transparency, multimodel agility, and actionability. Nag concludes, “Perplexity’s bet is that fact-checking transparency and agentic capabilities can capture enough high-value queries to build a sustainable business, even without toppling the giants.” Perplexity’s business model hinges on attracting users who prioritize reliability and verifiability over sheer ubiquity.
The Rise of Voice AI: Businesses Humanizing Chatbots
Another significant trend in the AI landscape is the rapid growth of voice AI, enabling businesses to create more human-like interactions with customers. This shift towards more natural and intuitive communication channels is reshaping customer service and engagement strategies across various industries.
Funding Surge in Voice AI
Voice AI startups experienced an eightfold increase in funding in 2024, driven by advancements in technology that facilitate real-time, humanlike voices. Companies like OpenAI and ElevenLabs are at the forefront of these advancements. The influx of capital reflects the growing recognition of voice AI’s potential to revolutionize customer interactions and streamline business operations.
Cost Reduction and Availability: The Business Benefits
Businesses are leveraging voice agents to reduce costs and enhance availability, starting with tasks such as after-hours calls and appointment scheduling. Voice AI allows companies to provide round-the-clock customer service without the need for extensive human staffing. By automating routine tasks and providing instant responses to customer inquiries, voice AI can significantly reduce operational expenses and improve customer satisfaction.
Challenges and Opportunities in Voice AI
Despite the increasing adoption of voice AI, challenges remain, particularly concerning accuracy and trust, especially in high-stakes or public-facing scenarios. Ensuring the reliability and accuracy of voice AI systems is critical for maintaining customer confidence. Addressing these challenges will require ongoing research and development in areas such as speech recognition, natural language processing, and contextual understanding.
Redefining Customer Communication: The Voice Revolution
A significant transformation is underway in customer communication, spearheaded by voice-based artificial intelligence (AI) agents. These agents are now outperforming traditional call centers and gradually replacing human labor across various industries, from healthcare to retail, according to venture capital firm Andreessen Horowitz. The rise of voice AI is not merely a technological advancement; it represents a fundamental shift in the way businesses interact with their customers.
The Power of Voice: A Programmable Medium
Olivia Moore, a partner at Andreessen Horowitz, emphasized the impact of voice AI, stating, “Voice is one of the most powerful unlocks for AI application companies. It is the most frequent and information-dense form of communication, made programmable for the first time due to AI.” The ability to program and automate voice interactions opens up a wide range of possibilities for businesses seeking to improve efficiency, enhance customer service, and drive revenue growth.
24/7 Customer Response: The Competitive Edge
Moore highlighted that voice AI allows businesses to provide 24/7 customer support, eliminating the limitations of traditional office hours. For consumers, voice interaction is becoming the primary way of engaging with AI. This always-on availability provides a significant competitive advantage in today’s fast-paced, customer-centric business environment.
Consumer Adoption of Voice Shopping
According to a PYMNTS Intelligence report, 30.4% of Gen Z consumers shop by voice every week, followed by millennials at 27.6%. Overall, an average of 17.9% of consumers use voice for shopping. The increasing adoption of voice shopping reflects the growing comfort and familiarity with voice-enabled devices and the convenience they offer.
Funding Boom in Voice AI Startups
Last year, voice AI startups raised $2.1 billion, an eightfold increase from 2023, driven by the advancements in voice AI models such as OpenAI’s Realtime API for speech-to-speech applications. These advancements have significantly boosted the capabilities of voice AI applications across various use cases. The substantial funding underscores the immense potential of voice AI to transform various industries and improve the way people interact with technology.
Voice AI Performance: Matching Human Capabilities
Alex Levin, co-founder and CEO of voice AI company Regal, commented on the recent improvements in voice AI, stating, “It’s really in the last 12 to 18 months that we’ve seen AI voice agents performing as well or better than humans.” The ability of voice AI agents to match or even exceed human performance in certain tasks is driving their rapid adoption across various industries.
Strategic Partnerships and Implementations
Major brands are integrating voice AI to enhance their services. Yum! Brands, including Taco Bell, KFC, and Pizza Hut, partnered with Nvidia to deploy AI solutions, including voice AI in call centers. Jersey Mike’s has implemented SoundHound’s AI for voice ordering in 50 stores. Additionally, SoundHound partnered with Allina Health to deploy “Alli,” an AI agent that manages patient appointments and will soon handle medication refills and non-clinical questions. These strategic partnerships and implementations demonstrate the growing confidence in voice AI’s ability to improve customer engagement, streamline operations, and drive business growth.
A Pivotal Moment: Advancements in Voice AI Infrastructure
The past year has witnessed radical improvements in the underlying AI infrastructure for voice. OpenAI introduced a “voice mode” built on GPT-4o, offering real-time voice responsiveness, interruption capabilities, and diverse emotional tones. ElevenLabs followed with Conversational AI, and companies like Kyutai and Speechmatics have brought real-time, full-duplex conversations into production. These advancements have significantly improved the quality, reliability, and versatility of voice AI applications.
Affordability and Latency Improvements
These models have also become more affordable, with OpenAI reducing GPT-4o API costs by up to 87.5% last December. Consequently, conversation quality is now largely a “solved problem,” and startups are deploying voice AI as an entry point into broader enterprise platforms. The improved affordability and reduced latency have made voice AI more accessible to businesses of all sizes, driving its widespread adoption.
Enterprise Adoption: Starting Small, Growing Big
Businesses are starting with simple implementations such as handling FAQs, booking appointments, and conducting initial screenings. Ketan Babaria, chief digital officer of insurance marketplace eHealth, noted that voice AI has become remarkably humanlike, making it difficult for customers to differentiate between AI agents and human representatives. The ability of voice AI agents to seamlessly integrate into existing workflows and provide a human-like experience is driving their rapid adoption across various industries.
The Future of Voice AI: Independent Task Execution
The next advancement involves AI voice agents capable of independently performing tasks such as making restaurant reservations, closing sales, and placing orders, according to PolyAI CEO Nikola Mrksic. The ability of voice AI agents to perform complex tasks autonomously will further revolutionize customer service and business operations.
Voice AI Use Cases
Voice AI is currently being used in various contexts:
- After-hours or overflow calls: Voice agents collect and share information, complete bookings, and handle transactions.
- Net-new outbound calls: Voice agents conduct customer check calls, activation calls, and lead calls.
- Back office calls: Voice agents manage calls to vendors and suppliers.
Hurdles and Risks
Despite the rapid adoption, voice AI still faces challenges. Reputational risk remains high, especially when systems fail in public. McDonald’s, for instance, discontinued its voice AI pilot with IBM after videos of incorrect orders went viral. These challenges highlight the importance of careful planning, testing, and monitoring to ensure the reliability and accuracy of voice AI systems.
Perplexity AI’s strategic focus on business needs and voice AI’s advancements in customer communication shows the transformative potential of AI in various sectors. Voice AI is rapidly evolving becoming a key component in business strategies to enhance communication, improve efficiency, and drive innovation in the dynamic world of AI.