Written by Phil Muncaster, guest writer at ESET (more…)

UiPath has acquired Peak, an AI-native company headquartered in Manchester, United Kingdom. The Peak AI platform enhances product inventory and pricing optimization for businesses across various industries, delivering fast, tangible results without requiring extensive in-house tech teams.

“With the acquisition of Peak, we are accelerating our mission to strengthen our vertical AI solutions strategy,” said Daniel Dines, Founder and CEO of UiPath. “When combined with the UiPath platform, Peak’s exceptional purpose-built AI applications will enhance our ability to provide solutions that optimize industry-specific use cases and deliver incredible value to customers.”

Peak empowers customers to create AI workflows, process data, and generate predictions that streamline critical business operations via APIs or integrated web applications. It also offers advanced AI-based decisioning tools, enabling business users to tackle complex tasks like inventory planning and product pricing optimization.

Now part of UiPath, Peak’s solutions gain the ability to scale globally and penetrate new industries, fostering growth and innovation for customers and stakeholders. Additionally, Peak’s emphasis on driving AI adoption in sectors such as retail and manufacturing will help UiPath expand its market presence and deliver cutting-edge, AI-driven, industry-specific applications powered by large language models (LLMs).

“Joining forces with UiPath is the perfect next step for Peak at this stage of our journey, and I couldn’t be more excited. As automation and agentic AI converge, we’re entering a new era of possibilities for the enterprise,” said Richard Potter, CEO & Co-Founder of Peak. “UiPath’s global reach, deep enterprise expertise, and unwavering commitment to AI innovation will enable us to accelerate our vision—empowering businesses with specialized decision-making AIs at scale. We are incredibly proud of what we’ve built, and as part of UiPath, we look forward to delivering even greater value to our customers while pushing the boundaries of what’s possible with AI in the enterprise.”

Peak is set to elevate the UiPath agentic automation platform, addressing the need for precise calculations in complex business processes. By delivering reliable analysis and predictions, Peak’s solutions will power UiPath’s new Pricing and Inventory Agents, ensuring businesses can make informed decisions. Additionally, Peak’s Decision Intelligence capabilities will enhance the platform’s orchestration features, enabling autonomous processes driven by contextual customer data.

With this collaboration, customers of both UiPath and Peak can achieve higher revenue and improved margins through their combined technologies. The partnership has already demonstrated success, such as transforming the quoting and pricing process for Heidelberg Materials, one of the world’s largest building materials manufacturers in the United Kingdom. The solution automates data collation from hundreds of sources, employs AI to determine optimal quotes, and equips sales teams with actionable insights. This streamlined, end-to-end process has significantly boosted efficiency, accelerating quotation times and increasing conversion rates.

Qlik has announced findings from an IDC survey exploring the challenges and opportunities in adopting advanced AI technologies. The study highlights a significant gap between ambition and execution: while 89% of organizations have revamped data strategies to embrace Generative AI, only 26% have deployed solutions at scale. These results underscore the urgent need for improved data governance, scalable infrastructure, and analytics readiness to fully unlock AI’s transformative potential.

The findings, published in an IDC InfoBrief sponsored by Qlik, arrive as businesses worldwide race to embed AI into workflows, with AI projected to contribute $19.9 trillion to the global economy by 2030. Yet, readiness gaps threaten to derail progress. Organizations are shifting their focus from AI models to building the foundational data ecosystems necessary for long-term success.

Stewart Bond, Research VP for Data Integration and Intelligence at IDC, emphasised, “Generative AI has sparked widespread excitement, but our findings reveal a significant readiness gap. Businesses must address core challenges like data accuracy and governance to ensure AI workflows deliver sustainable, scalable value.” Without addressing these foundational issues, businesses risk falling into an “AI scramble,” where ambition outpaces the ability to execute effectively, leaving potential value unrealized.

“AI’s potential hinges on how effectively organizations manage and integrate their AI value chain,” said James Fisher, Chief Strategy Officer at Qlik. “This research highlights a sharp divide between ambition and execution. Businesses that fail to build systems for delivering trusted, actionable insights will quickly fall behind competitors moving to scalable AI-driven innovation.”

The IDC survey uncovered several critical statistics illustrating the promise and challenges of AI adoption: Agentic AI Adoption vs. Readiness:

• 80% of organizations are investing in Agentic AI workflows, yet only 12% feel confident their infrastructure can support autonomous decision-making.
• “Data as a Product” Momentum: Organizations proficient in treating data as a product are 7x more likely to deploy Generative AI solutions at scale, emphasizing the transformative potential of curated and accountable data ecosystems.
• Embedded Analytics on the Rise: 94% of organizations are embedding or planning to embed analytics into enterprise applications, yet only 23% have achieved integration into most of their enterprise applications.
• Generative AI’s Strategic Influence: 89% of organizations have revamped their data strategies in response to Generative AI, demonstrating its transformative impact.
• AI Readiness Bottleneck: Despite 73% of organizations integrating Generative AI into analytics solutions, only 29% have fully deployed these capabilities.

These findings stress the urgency for companies to bridge the gap between ambition and execution, with a clear focus on governance, infrastructure, and leveraging data as a strategic asset.

The IDC survey findings highlight an urgent need for businesses to move beyond experimentation and address the foundational gaps in AI readiness. By focusing on governance, infrastructure, and data integration, organizations can realize the full potential of AI technologies and drive long-term success.