Adobe has acquired India-based marketing intelligence startup Rilo in a deal that combines technology licensing with the acquisition of the startup’s six-member team, giving the software giant additional technology for automating increasingly complex marketing and customer-experience workflows.

The financial terms were not disclosed. Adobe confirmed the acquisition but declined to provide further details.

The transaction marks Adobe’s second acquisition from India after the company bought video technology startup Rephrase.ai in 2023, and comes as Adobe intensifies its push to integrate artificial intelligence into its marketing, creative and customer-experience products.

Rilo was founded in 2025 by Indian Institute of Technology alumni Georgi Boby and Dhruv Jaglan. The startup raised $1 million from Peak XV Partners, DeVC and Day Zero Ventures at a reported valuation of $10 million.

A source told TechCrunch that Rilo’s investors will receive an exit as part of the transaction, while Adobe plans to incorporate some of Rilo’s intellectual property into its products. Rilo itself will shut down following the acquisition, and its service will no longer be available to existing customers.

The startup developed software designed to allow go-to-market teams to build and automate customized workflows covering tasks such as competitor intelligence, content repurposing and distribution, and sales-call analysis.

Its technology also allowed businesses to construct workflows similar to those emerging around AI agents, enabling software to move beyond generating content or answering questions and instead execute sequences of tasks based on instructions.

That capability is expected to become a big boost to Adobe as businesses seek to automate marketing operations across multiple stages of a campaign, from content creation and distribution to performance monitoring and follow-up actions.

Adobe Targets The Next Phase Of AI-Powered Marketing

The acquisition reflects a broader shift in enterprise software toward agentic workflows, where AI systems can coordinate multiple tasks rather than operate as standalone assistants.

Marketing teams, for example, now want AI systems that can analyze a sales call, identify follow-up actions, generate appropriate content, distribute that content across relevant channels, and monitor the resulting engagement. Companies are also looking for tools that can track how their brands appear in responses generated by AI assistants such as ChatGPT, Gemini and Claude.

Rilo’s workflow technology could give Adobe additional infrastructure for addressing those requirements within its broader customer-experience and marketing ecosystem.

Rahul Mathur of DeVC said Rilo could fit into Adobe’s customer-experience and marketing products by handling complex workflows and giving customers greater visibility into actions performed across Adobe’s platform.

The strategic value for Adobe therefore extends beyond acquiring a six-person team. The company is gaining intellectual property that could accelerate development of AI-driven automation without having to build every component internally.

Rahul Gupta, managing partner at Day Zero Ventures, said Rilo’s workflow-builder technology was “way ahead of the curve” and could help Adobe improve customer experience and productivity.

Adobe has been expanding its marketing technology portfolio through acquisitions as it attempts to connect its creative tools with the increasingly automated digital-marketing stack.

In 2025, the company agreed to acquire SEO and digital-marketing platform Semrush for $1.9 billion. That transaction gave Adobe access to technology focused on search visibility, content optimization, and digital marketing intelligence.

Rilo adds a different layer to that strategy: workflow automation.

The combination could potentially allow Adobe to move from helping customers create and optimize marketing content toward helping them automate the operational processes surrounding that content.

AI has been changing how marketing organizations are structured. Generative AI has made content production faster, but businesses still need systems capable of deciding what should be produced, where it should be distributed, who should act on the results, and how performance should be measured.

Adobe’s broader opportunity is to make its Creative Cloud, Experience Cloud and AI capabilities part of that automated workflow.

Competition Is Intensifying

Adobe is not pursuing this market alone.

Canva has expanded its marketing capabilities through acquisitions and new product development, while Amazon, Google and Meta have built sophisticated AI-powered advertising and marketing infrastructure.

The competition is shifting from individual creative and advertising applications toward integrated AI systems that can manage larger portions of the marketing lifecycle.

This creates both an opportunity and a strategic challenge for Adobe. Its existing customer base provides a major distribution advantage, but the company must ensure that AI agents and workflow tools become deeply integrated into products customers already use rather than emerging as disconnected features.

Rilo’s technology could help accelerate that transition.

The acquisition also underpins the growing importance of India’s startup ecosystem as a source of specialized AI and enterprise software talent. Rilo was founded only in 2025 and raised $1 million before being acquired, illustrating how quickly large technology companies are moving to absorb small teams with technology aligned with strategic AI priorities.

The transaction is ultimately less about Rilo’s existing customer base, which will disappear with the shutdown of the startup, than about its technology and people. Adobe is effectively buying a compact engineering team and intellectual property that could be incorporated into a much larger software platform.

As Adobe competes to make AI a central layer of its marketing and customer-experience business, acquisitions such as Rilo’s could provide a faster route to agentic automation while allowing the company to leverage its existing enterprise distribution and customer relationships.

Palo Alto Networks Chief Executive Nikesh Arora said Tuesday that the rapid adoption of artificial intelligence is forcing companies to reconsider roughly $1 trillion of cybersecurity infrastructure built for a pre-AI environment, as automated attacks increasingly operate at speeds that legacy defenses were never designed to handle.

“Nothing that was deployed seven or 10 years ago is prepared or ready to handle AI at machine speed,” Arora told CNBC’s Jim Cramer on “Mad Money.” “You have to rethink your cyber architecture.”

He made the assertion as Palo Alto reported quarterly results that beat Wall Street expectations and issued a strong outlook for its new fiscal year, suggesting that the security spending Arora describes as necessary is already beginning to translate into commercial demand.

The company estimates that there is approximately $1 trillion in accumulated global “cybersecurity debt” that organizations will need to modernize to defend against automated threats.

“There’s approximately $1 trillion of global cybersecurity debt that must be modernized to defend against automated threats because they operate instantaneously,” Arora said on Palo Alto’s earnings call.

The argument marks a notable shift in the market’s perception of AI and cybersecurity.

Earlier this year, cybersecurity stocks came under pressure as investors worried that capable AI models could automate security functions, reduce demand for conventional cybersecurity software and ultimately disrupt established vendors.

That concern has increasingly given way to a different view: AI is becoming a force multiplier for both attackers and defenders. The same technology that can help security teams identify vulnerabilities and automate responses can also enable attackers to discover weaknesses, develop exploits, and move across networks far faster than human operators.

“You cannot deploy AI successfully if you don’t get cybersecurity right,” Arora said.

From AI Threat to AI Growth Opportunity

Arora described the change in investor sentiment as a dramatic reversal from earlier in the year.

“Nine months ago, … we were guilty and convicted of near death because AI was going to eat our lunch, breakfast, and dinner,” he told Cramer. “It seems like that’s not the case. It seems like we’re going to have to have the feast with them.”

He identified the emergence of Anthropic’s Mythos model earlier this year as an important turning point in the industry’s thinking. The model demonstrated how advanced AI could be applied to cybersecurity operations, including the identification and exploitation of software vulnerabilities, intensifying concerns among businesses about whether their existing defenses could withstand machine-driven attacks.

“I’ve been trying for eight years to tell customers they’re not ready, and [Anthropic CEO Dario Amodei] did it in one event, just by launching Mythos,” Arora said.

Palo Alto’s stock has gained 113% since April 7, reversing losses accumulated earlier in 2026 as investors reassessed the impact of AI on the cybersecurity industry.

The change in sentiment reflects a broader realization that AI does not necessarily eliminate the need for cybersecurity software. Instead, it can increase the volume, speed, and sophistication of attacks, potentially expanding the amount companies need to spend to protect increasingly automated and interconnected systems.

Palo Alto Targets Legacy Infrastructure

Arora said Palo Alto has spoken with roughly 2,000 companies about its Frontier AI Critical Defense Program, an initiative designed to use advanced AI models to test corporate defenses, uncover vulnerabilities and help organizations modernize their security architecture.

Palo Alto formally introduced the programme in August.

The initiative is aimed at a growing problem for corporate IT departments: many security systems were designed around threats that moved at human or network speeds, while AI-enabled attacks can potentially scan environments, identify weaknesses and attempt exploitation almost instantaneously. That creates a widening gap between the speed at which an organization can detect and respond to a threat and the speed at which an automated attacker can exploit it.

For companies deploying AI agents that can access internal systems, customer information, financial data, or business applications, the stakes are even higher. A security failure could potentially give an autonomous system a pathway into sensitive corporate infrastructure, turning AI adoption itself into a new attack surface.

Opportunity Will Take Years to Materialize

Arora cautioned that the projected $1 trillion opportunity should not be interpreted as an immediate spending surge.

“Not everything’s going to happen next quarter,” he told Cramer. “But all I say is this changes the long-term growth rate and duration of cybersecurity, not just for Palo Alto, but as an industry.”

The opportunity will likely emerge through years of replacing legacy systems, deploying AI-specific security controls, and integrating cybersecurity into new AI infrastructure rather than through a single wave of spending. It also suggests that cybersecurity could become a prerequisite for enterprise AI deployment rather than a separate IT expense.

As companies increasingly use AI agents capable of taking actions without constant human supervision, security architecture will have to evolve from simply protecting users and devices to controlling what autonomous systems can access, execute, and modify.

Palo Alto’s strong results and outlook indicate that investors are beginning to price in that structural shift. The company’s central thesis is that AI may not be the technology that displaces cybersecurity; instead, it could be the technology that makes a much larger cybersecurity investment unavoidable.