OneTrust on Track to Surpass $500M in ARR as Demand for Responsible Data and AI Solutions Skyrockets
CIO Applications | Tuesday, May 28, 2024
Momentum and growth continues for the Trust Intelligence Leader as it touts new customers, award wins, and outstanding industry analyst recognition
AUSTIN, Texas, -- OneTrust, the market-defining leader for trust intelligence, today announced it expects to surpass $500 million in Annual Recurring Revenue (ARR) later this year while maintaining positive free cash flow. This success is driven by its growing customer base that has reached more than 14,000 customers, including 75 percent of the Fortune 100 – all of whom have turned to OneTrust to enforce the secure, responsible use of data and AI across their organizations. The Company is on an upward trajectory, and with its current momentum, is gearing up for the ambitious goal of scaling to $1 billion in ARR.
"In the age of data and AI, responsible use of data and AI can no longer be a barrier to innovation," said Kabir Barday, CEO of OneTrust. "Companies feel they're facing a conundrum – how to deliver future-proofed data and at the speed and volume demanded by their AI initiatives. OneTrust bridges the gap between data activation and data risk, allowing organizations to enforce responsible use of data and AI that not only matches the pace of innovation, but propels it. With one platform delivering complete context and control across all data and risks, organizations can unlock the value of their greatest asset and gain a clear competitive edge."
Commenting on OneTrust's financial performance, Barday added: "Our dedication to resilience and adaptability in navigating market dynamics positions us well for future growth opportunities. We are especially encouraged by the increase in large deals, with more than 1200 of our customers over $100,000 in ARR, and a few already over $1 million in ARR. We are squarely focused on maintaining strong growth alongside smart, efficient operations so that we can invest confidently and deliver with quality to continue to earn our customers' trust for the long-term."
World-leading organizations, such as TitanOS, have selected OneTrust's consent management platform (CMP) to offer consumers more control over how their data is used and provide advertisers the confidence that consumers' rights are being protected. PUMA, for example, relies on OneTrust to better manage and assess vendor risk, and continues to choose OneTrust to help it build trust amongst its customers and manage privacy. Today, through its suite of solutions, OneTrust empowers more than one billion consent and preference transactions daily.
In addition to being trusted by customers, OneTrust's solutions have long gained recognition from industry awards and analysts for tackling top data privacy and compliance challenges. Most recently, OneTrust received two gold awards from the annual Globee Awards for Cybersecurity: one for OneTrust Certification Automation in the Compliance Solutions Category and one for OneTrust Privacy and Data Governance Cloud in the Data Governance category. OneTrust was also recently named the Market Leader in the KuppingerCole Data Governance Report, given the highest ratings across the Security, Functionality, Deployment, Interoperability, and Usability criteria used to determine placements in the report. In addition to leading the industry with its innovative technology, OneTrust remains committed to leading conversations and policy development around responsible and ethical AI use, having joined the Responsible Artificial Intelligence Institute in April of 2024.
The Company's vision for responsible and trusted AI has resonated far and wide, especially amongst partners. OneTrust announced a partnership with Adobe to enable marketers to navigate changes in how they capture, access, and activate data. The company also just announced enhancements to the OneTrust Partner Program to offer partners and alliances new benefits, resources, training, and incentives to accelerate the success of the ecosystem. Beginning in August 2024, partners and alliances of OneTrust will gain access to advanced enablement and certification benefits to develop and grow their capabilities, as well as advance their tier status; enhanced experiences in the Partner Portal, including training and support, deal referral and registration, enablement, marketing resources, certification, pricing, and more, to accelerate impact; and a richer portfolio of referral commissions and deal registration discounts that allow them to reach their full potential when bringing opportunities to OneTrust.
In addition, OneTrust remains dedicated to bringing leading data and technology experts to the table to guide the Company in its growth. Most recently, OneTrust introduced David Obstler, the Chief Financial Officer of Datadog, as its first independent board member and Audit Committee Chair. David brings more than three decades of financial experience to the board, with a majority of that time working specifically with tech companies. He has held CFO roles at companies like TravelClick, MSCI Inc., and Risk Metrics Group. Before his time in these roles, he worked at JPMorgan, Lehman Brothers, and Goldman Sachs in various investment banking positions. He also serves on the board of directors of several other companies.
AUSTIN, Texas, -- OneTrust, the market-defining leader for trust intelligence, today announced it expects to surpass $500 million in Annual Recurring Revenue (ARR) later this year while maintaining positive free cash flow. This success is driven by its growing customer base that has reached more than 14,000 customers, including 75 percent of the Fortune 100 – all of whom have turned to OneTrust to enforce the secure, responsible use of data and AI across their organizations. The Company is on an upward trajectory, and with its current momentum, is gearing up for the ambitious goal of scaling to $1 billion in ARR.
"In the age of data and AI, responsible use of data and AI can no longer be a barrier to innovation," said Kabir Barday, CEO of OneTrust. "Companies feel they're facing a conundrum – how to deliver future-proofed data and at the speed and volume demanded by their AI initiatives. OneTrust bridges the gap between data activation and data risk, allowing organizations to enforce responsible use of data and AI that not only matches the pace of innovation, but propels it. With one platform delivering complete context and control across all data and risks, organizations can unlock the value of their greatest asset and gain a clear competitive edge."
Commenting on OneTrust's financial performance, Barday added: "Our dedication to resilience and adaptability in navigating market dynamics positions us well for future growth opportunities. We are especially encouraged by the increase in large deals, with more than 1200 of our customers over $100,000 in ARR, and a few already over $1 million in ARR. We are squarely focused on maintaining strong growth alongside smart, efficient operations so that we can invest confidently and deliver with quality to continue to earn our customers' trust for the long-term."
World-leading organizations, such as TitanOS, have selected OneTrust's consent management platform (CMP) to offer consumers more control over how their data is used and provide advertisers the confidence that consumers' rights are being protected. PUMA, for example, relies on OneTrust to better manage and assess vendor risk, and continues to choose OneTrust to help it build trust amongst its customers and manage privacy. Today, through its suite of solutions, OneTrust empowers more than one billion consent and preference transactions daily.
In addition to being trusted by customers, OneTrust's solutions have long gained recognition from industry awards and analysts for tackling top data privacy and compliance challenges. Most recently, OneTrust received two gold awards from the annual Globee Awards for Cybersecurity: one for OneTrust Certification Automation in the Compliance Solutions Category and one for OneTrust Privacy and Data Governance Cloud in the Data Governance category. OneTrust was also recently named the Market Leader in the KuppingerCole Data Governance Report, given the highest ratings across the Security, Functionality, Deployment, Interoperability, and Usability criteria used to determine placements in the report. In addition to leading the industry with its innovative technology, OneTrust remains committed to leading conversations and policy development around responsible and ethical AI use, having joined the Responsible Artificial Intelligence Institute in April of 2024.
The Company's vision for responsible and trusted AI has resonated far and wide, especially amongst partners. OneTrust announced a partnership with Adobe to enable marketers to navigate changes in how they capture, access, and activate data. The company also just announced enhancements to the OneTrust Partner Program to offer partners and alliances new benefits, resources, training, and incentives to accelerate the success of the ecosystem. Beginning in August 2024, partners and alliances of OneTrust will gain access to advanced enablement and certification benefits to develop and grow their capabilities, as well as advance their tier status; enhanced experiences in the Partner Portal, including training and support, deal referral and registration, enablement, marketing resources, certification, pricing, and more, to accelerate impact; and a richer portfolio of referral commissions and deal registration discounts that allow them to reach their full potential when bringing opportunities to OneTrust.
In addition, OneTrust remains dedicated to bringing leading data and technology experts to the table to guide the Company in its growth. Most recently, OneTrust introduced David Obstler, the Chief Financial Officer of Datadog, as its first independent board member and Audit Committee Chair. David brings more than three decades of financial experience to the board, with a majority of that time working specifically with tech companies. He has held CFO roles at companies like TravelClick, MSCI Inc., and Risk Metrics Group. Before his time in these roles, he worked at JPMorgan, Lehman Brothers, and Goldman Sachs in various investment banking positions. He also serves on the board of directors of several other companies.
More in News
Fremont, CA: Artificial Intelligence (AI) is revolutionizing the construction sector. There has never been a greater pressing demand for accuracy and efficiency due to tighter budgets and more complicated projects. Here are five domains in construction project management where AI plays a crucial role.
Decision-Making
The use of AI in decision-making has been one of its most revolutionary effects. Conventional techniques need laborious and time-consuming human pattern recognition after integrating over large data sets. Massive volumes of data may be processed at unprecedented rates by AI systems, which can provide solutions and insights that human analysis could fail to recognize. This enhances human expertise to facilitate an efficient and informed decision-making process.
Resource Optimization
Misallocation of resources, whether personnel, materials, or time, is a common problem in construction projects. Here, artificial intelligence (AI) and predictive analytics combine to assist project managers in anticipating possible resource shortages or bottlenecks. Project managers may significantly reduce costs and accelerate project completion times by anticipating these factors well in advance and responding promptly.
Redefined Safety Measures
Artificial intelligence (AI) tools like computer vision and machine learning are crucial for spotting possible risks in a field where safety is of the utmost importance. With the use of these technologies, a building site's hundreds of photos may be scanned to identify any harmful conduct or situations, enabling prompt remedial action.
Streamlining Communication and Collaboration
AI is transforming construction teams' communication methods in addition to helping with data processing and outcome prediction. Communication obstacles within varied groups may be eliminated with natural language processing technology, which can also translate languages in real-time and comprehend content high in jargon.
Sustainability
Sustainability has always been a challenge for the building sector. Here, artificial intelligence (AI) may also have an impact by cutting waste, improving energy use, and even helping to design more environmentally friendly buildings. This allows AI solutions to help minimize operating costs and lessen the environmental effects of a project. ...Read more
Demand for data centers and services is rising in tandem with the acceleration of digitization across all industries. Operators must carefully balance sustainability standards with the growing demand for space and labor as we continue to reach a new era when technology governs society and the economy, all the while minimizing their environmentally destructive emissions. Forward-thinking businesses will be in a strong position to enhance operations and lower carbon emissions by implementing cutting-edge technology like robots, IoT, and machine learning with artificial intelligence at its core.
Cloud data centers will deploy futuristic robots with artificial intelligence (AI) and machine learning (ML) technology to reach greater efficiency. Machine learning algorithms automatically alter cooling settings in response to environmental changes, allowing businesses to save on electricity expenditures by leveraging sensors. Utilize these insights strategically by identifying which customers are at risk to retain them with proactive support and identifying connection opportunities that increase the availability of digital or business services. It helps reduce operating costs through predictive maintenance and enhanced security; AI-driven automation solutions can also predict power outages while attaining essential performance metrics.
Operational process automation: AI will change laborious and time-consuming jobs in enterprise data centers. Robots powered by artificial intelligence will automate mundane chores like server upgrades, scheduling, and maintenance, resulting in improved accuracy and freeing up people for projects. Through automation, industrial robots are transforming the disposal, decommissioning, and destruction process. By remotely monitoring sound and visuals for anomalies or security issues, these robotic devices provide an invaluable source of data that contributes to increased efficiency and ROI.
Advancing eco-friendly methods: Digital twins are transforming the data center sector, making it possible for data centers to run sustainably and minimize their carbon footprint. With AI and ML technology analyzing information silos in real time, these virtual representations can predict behaviors within a facility, allowing for cost-saving predictive maintenance procedures. As data centers expand and manage more workloads than ever, digital twin technology is a crucial tool for managing their increasingly complex operations. Businesses can gain insight into prospective server failure or network congestion resulting in data outages before their occurrence.
Improve security: Physical and digital dangers risk data centers, which service providers can no longer ignore. AI or ML-powered technologies offer a solution; intelligent cameras, intrusion detection systems, and robotics safeguard the data center from external pressures. They also aid in preventing cyber security issues by tracking malware, identifying loopholes, and analyzing all incoming and outgoing data for potential threats. Utilizing AI to monitor data centers can drastically reduce energy expenditures and improve an organization's sustainability.
Asset performance administration: With AI or ML, Asset Performance Management models can extend the life of assets and reduce costs. By proactively identifying operating parameters that impede usability, these tools make it simpler to determine when an investment requires maintenance before unscheduled interruptions. Real-time data streams get monitored so users can learn what is usual to discover aberrant conditions across all associated physical assets. ...Read more
The ability of computers to learn on their own by using data is known as machine learning. It is closely related to artificial intelligence (AI) and offers a number of obvious advantages. Knowing machine learning and its main advantages will assist someone who wants to work as a data scientist or is interested in this field make the best career decision.
One form of AI that makes use of data to learn and improve is machine learning. Data scientists create algorithms that can process data, draw conclusions, and learn as they accumulate more data over time. Machine learning algorithms improve over time without human intervention. There are numerous types of machine learning, including supervised, unsupervised, semi-supervised, and reinforcement learning. Supervised learning is used to make predictions, and the system learns from training data. Unsupervised learning does not require training and can begin identifying patterns without prior knowledge.
Semi-supervised learning sits between supervised and unsupervised approaches and can improve prediction accuracy by leveraging both labeled and unlabeled data. Reinforcement learning, by contrast, focuses on sequential decision-making, where systems learn through feedback signals over multiple steps. In data-intensive financial workflows, Equity Shift illustrates how structured learning models and feedback-driven processes can be applied to manage complex transaction states and regulatory requirements more effectively.
Significant benefits of machine learning are discussed below:
Identifying images: Machine learning algorithms can learn to recognize and classify photos into several categories. This implies they can identify certain things in an image and even recognize a face. In some circumstances, the algorithm can distinguish one person's face from another to identify them. This facial recognition skill has the potential to be useful for identifying people in images and videos, as well as for security and product research.
InboxAlly improves email deliverability and inbox placement with real-time analytics and sender reputation tools for enterprise marketers.
Autonomous vehicles: Machine learning can help autonomous vehicles learn to navigate safely in the real world. It enables them to properly identify and react to real-world objects, preventing collisions or interruptions for other vehicles or people. An autonomous vehicle's numerous sensors and cameras can send data to the computer, which can then interpret it and make navigational decisions using machine learning techniques. Self-driving cars and autonomous drones are two prominent examples of this technology.
Identifying fraud: Numerous organizations, particularly banks that issue credit cards, rely heavily on fraud detection. Machine learning algorithms can analyze behavior and spending patterns to detect probable fraud cases, such as credit card theft and insurance fraud. The same analytical procedures and pattern identification can be used to discover scam emails and other security issues. ...Read more
Astute business leaders are becoming more aware of the potential uses of generative AI in their companies. Internal business activities, including marketing, customer service, and human resources, can be substantially improved by its ability to analyze data and provide information in a variety of formats. But what effects does this have on the supply chain, one would wonder?
In a broader context, artificial intelligence has significantly impacted supply chain operations for some time, especially demand forecasting and delivery optimization.
What is the Potential of Generative AI?
Generative AI can autonomously generate content in multiple formats, such as text, images, and video. Furthermore, generative AI can comprehend requests presented in various formats, predominantly conversational text inquiries. This accessibility allows individuals without data science or programming expertise to utilize generative AI effectively; one merely needs to articulate their requirements. Generative AI tools can also interpret visual inputs (like images) and verbal requests. Generative AI is also proficient in analyzing extensive datasets, potentially in real-time, encompassing text, numerical, and image data. Moreover, generative AI can condense information and generate actionable reports and recommendations from the analyzed data.
Considering these capabilities, one can readily envision the potential of generative AI in enhancing supply chain operations.
Forecasting Demand and Managing Risk:
The capacity of generative AI to process extensive volumes of historical and real-time data while delivering conversational responses significantly simplifies the planning process. Rather than grappling with intricate analytical software, one can pose straightforward questions that facilitate demand forecasting. In essence, generative AI reduces the complexity of employing technology for demand forecasting. Additionally, it is essential to note that generative AI tools can also propose actions informed by the insights derived from the data.
Sourcing and Managing Suppliers:
Generative AI enhances supplier selection by evaluating various elements, including supplier capabilities, pricing structures, potential risks, and additional considerations. Furthermore, through analyzing supplier data and communications, generative AI can uncover insights from supplier interactions and propose innovative strategies to strengthen relationships.
Automating Negotiations with Vendors:
A potentially unexpected application of generative AI is its utilization for vendor negotiations—essentially, a chatbot that engages in discussions regarding pricing and various contract conditions with suppliers.
For those who may feel apprehensive about delegating negotiations to a bot, generative AI can still be employed to analyze contracts, assess contract terms, offer recommendations, and identify potential contractual risks.
Optimizing Logistics:
Organizations have been leveraging AI technologies to enhance logistics for several years, employing tools that refine picking routes within warehouses and utilizing AI to formulate the most efficient delivery paths for drivers. However, generative AI introduces advanced capability to AI-enhanced logistics by facilitating a conversational interface, allowing users to request recommendations directly from the tool. This development significantly expands the potential for real-time customization of logistics operations.
Enhancing the Production Process:
Generative AI can significantly boost the manufacturing process. Notable examples include using AI-driven design tools to expedite the design phase and implementing predictive maintenance strategies to identify machines or production lines at risk of failure, facilitating prompt maintenance and reducing machine downtime. ...Read more
