Three Developments Worth Watching

1. SentinelOne and Lenovo extend AI security: Integrating prompt protection into enterprise security offerings addresses growing risks from unauthorized AI use and data exposure.
2. Cognizant introduces AI Nexus: Managing AI costs, quality and outcomes becomes increasingly important as enterprises expand deployment.
3. Nutanix and Netris combine cloud infrastructure capabilities: Automated networking and multitenancy could help providers deliver secure GPU-based services more efficiently.

These developments demonstrate that successful AI adoption requires more than access to models. Enterprises need coordinated infrastructure, measurable performance and security controls that extend across the AI lifecycle.

5 IT and Technology News Stories

1. SentinelOne and Lenovo Extend Collaboration With AI Agent Security Capabilities

SentinelOne and Lenovo are expanding their partnership by integrating SentinelOne Prompt Security into Lenovo’s ThinkShield Security Portfolio, adding AI discovery, prompt protection and data loss prevention capabilities.

As employees increasingly use generative AI and autonomous agents, conventional endpoint security may not adequately address sensitive information entering external AI tools. Embedding AI governance into existing enterprise security offerings could help organizations adopt AI without relying on blanket restrictions. The challenge will be maintaining visibility across approved and unauthorized tools while ensuring policies keep pace with increasingly autonomous systems.

2. Cognizant AI Nexus Redefines Enterprise AI Infrastructure Governance

Cognizant AI Nexus focuses on helping enterprises govern AI costs, quality and outcomes as they deploy AI across business operations and technology environments.

As organizations expand AI adoption, fragmented deployments can make it difficult to track spending, compare model performance and demonstrate business value. A coordinated governance approach could help IT leaders make better infrastructure decisions and identify underperforming investments. The broader opportunity is to shift enterprise AI management from experimentation towards measurable operational outcomes. However, governance frameworks must provide actionable visibility without creating additional complexity for teams already managing diverse technology environments.

3. Nutanix and Netris Introduce Integrated Multitenant Infrastructure for AI Clouds

Nutanix and Netris are developing an integrated infrastructure stack combining compute orchestration, virtualization and network automation to support secure, multitenant GPU services for neocloud operators and enterprise data centers.

Demand for AI computing is increasing pressure on providers to deliver GPU capacity with reliable isolation, networking and self-service provisioning. Automating these layers could shorten deployment cycles and help providers monetize infrastructure more efficiently. For enterprise customers, stronger workload isolation may also support more secure shared environments. Commercial success will depend on interoperability, predictable performance and the economics of operating GPU-intensive services at scale.

4. Cloudflare Expands Its AI Workspace Platform

Cloudflare is expanding its AI Workspace ecosystem through partnerships designed to connect AI applications, edge inference, vector search, storage and enterprise security controls.

Businesses deploying AI assistants often encounter latency, fragmented data pipelines and concerns about exposing proprietary information to external models. Combining these capabilities within a connected platform could simplify development and improve access to enterprise knowledge. Edge-based inference may also benefit applications requiring responsive interactions. However, enterprises will need to assess model suitability, data residency, security controls and total operating costs before deciding which workloads belong at the edge or in centralized cloud environments.

5. S&P Global Strengthens Private Markets Analytics With New AI Capabilities

S&P Global is expanding its AI capabilities across private markets analytics, supporting investment professionals seeking deeper insights from complex financial and portfolio information.

Private markets involve fragmented data, extensive documentation and limited transparency compared with publicly traded assets. AI-powered analysis could help investors identify relevant information faster, evaluate portfolio risks and improve research workflows. Yet financial decisions require traceability and reliable underlying data. The competitive advantage will depend on whether these capabilities deliver verifiable insights while preserving confidentiality and analytical rigor, rather than simply accelerating document processing.

ITDigest Featured Article

Essential Enterprise IT Service Management Tools: How to Choose the Right ITSM Platform

The article examines how enterprises can select IT service management platforms based on workflow automation, incident resolution, asset visibility, integration and scalability. It highlights the importance of aligning platform capabilities with organizational requirements, service quality and budgets. As AI enters IT operations, businesses should also evaluate governance, usability and measurable improvements in service delivery.

The post ITDigest Weekly Roundup: AI Agent Security, Governed Enterprise Intelligence and the Next Phase of Cloud Infrastructure appeared first on ITDigest.

Also Read: Tanium Extends Enterprise Endpoint Management to NVIDIA’s On-Premises AI Infrastructure

With Web Archive, there are plans to enhance the ability to capture dynamic and browser-generated content. This way, the organization will have the ability to archive its changing digital experience. Cyber Compliance offers organizations visibility of security postures of personal and unmanaged devices connected to business applications, while Vendor Risk Management consolidates all vendor assessments, risk scores, remediation efforts, and reassessments.“Risk does not arrive in one system or on one schedule,” said Kamesh Tumsi, Chief Product Officer at Smarsh. “Small and mid-sized financial services firms need a practical way to understand what is changing across their communications, devices, and third parties without adding unnecessary complexity. These capabilities help lean teams focus their expertise where it matters most and maintain a clear record of the actions they take.”

Read More: Smarsh Expands Solutions for AI, Cyber, and Third-Party Risk

The post Smarsh Strengthens Compliance With Expanded AI and Cybersecurity Solutions appeared first on ITDigest.

Consolidate incidents, service requests, assets, and workflows into a single, integrated platform. But weighing features makes choosing the best enterprise ITSM tool challenging; we’ve examined it and others to help organizations optimize service delivery in terms of accuracy and on the lowest-cost.

Core Capabilities of a Modern Enterprise ITSM Platform

What are current enterprise IT service management (ITSM) solutions capable of? Beyond logging service desk tickets, modern solutions bring together incident resolution, service requests, asset management, change management, and automation within a single platform. Through integration with ITIL, the right tool will allow an IT team to standardize delivery, prevent recurring problems, and reduce unplanned downtime. Here are five key areas to consider.

Incident Management and Problem Resolution

When an incident occurs, incident management deals with the repairs. The practice, however, also examines the cause of the incident to understand the reason behind repeated failures. This shift of focus allows teams to move beyond applying the same solutions again and again and reach the root cause of eruptions. The CISA Known Exploited Vulnerabilities Catalog can also shed light on a vulnerability-management approach.

Service Request Fulfillment

How they are assisted They require ongoing assistance in using their applications and programs for e.g. software to access, password resets, hardware, and user rights. Automated service portals enable them to make a request, track its progress and view a knowledge base so they don’t have to contact support. Automated approval routings enable IT to fulfill requests using an explicit workflow with limited user effort.

Change and Configuration Management

IT improvements can cause a change in issue if the teams would not have the visibility of the way the IT systems are linked with each other. CMDB (Configuration Management Database): This CMDB stores the major IT assets along with their relation with other assets, so that the teams could analyze the impact of change before change. As per the guidelines of NIST on asset management and visibility, the organization places emphasis on asset discovery, asset inventory, asset configuration, and asset changes for operational technology environments.

IT Asset Management

ITAM manages assets 1 and 2 from their procurement or creation, through their deployment, renewal, and until their cessation. Accurate records mean teams can find unnecessary licenses, see who is actually using the software, plan replacements, and understand who is responsible for what with a better understanding of ongoing compliance commitments. Linking to service management means support teams can see asset-to-user and asset-to-incident relationships.

Workflow Automation and AI

AI automation can help sequence tickets, prioritize, initiate approvals, and answer common questions on a chatbot interface. More sophisticated agentic workflows can sequence multiple steps, and require organizations to still have well understood permissions and human oversight for delicate actions. NIST has an ongoing investigation, until September 2026, on software and agentic AI identity1, to learn about how AI agents can be identified, authenticated, and authorized in the software development lifecycle.

Also Read: Future of Digital Payments: How Fintech Disruption Is Reshaping the Global Financial Ecosystem

A Closer Look at Leading Enterprise ITSM Tools

Buyers are encouraged to determine whether the platform suits their operating model and integration requirements and whether it aligns with its own internal IT maturity rather than trying to compare feature for feature. The enterprise ITSM market has platforms for those operating thousands of assets within large organizations, to those growing their business.

Enterprise Titans

Recommended for Organizations looking for robust service-management capabilities with extensive configuration management and workflow within a large IT footprint. Market differentiator Management of integrations and workflows at scale. Know this The scope of implementation, customization, and administration considerations is substantial.

Developer-Focused and Agile Platforms

Jira Service Management from Atlassian for teams that associate IT support with other Dev Ops development projects. But it benefits from a natural position among the rest of the Atlassian applications in sharing incident, change, and service request data. Buyers should consider how well its setup and controls support the enterprise more generally.

Mid-Market Powerhouses

Manage Engine Service Desk Plus, Ivanti and Freshservice are options for those whose organization intends to formalize service management as it matures. In some cases they could be easier to implement, depending on the product configuration and how the customer’s system is already set up. Buyers may need to compare integration levels, asset management, automation, reporting and licensing.

Gartner’s ITSM Platform Magic Quadrant, 27 July 2026 By Gartner 16 Vendors in Total Public abstract: ITSM platforms are the systems of record for I&O leaders to leverage that registers the event and activity data for service management and drives delivery of an integrated IT service experience. While an interesting perspective for comparing vendors, the ultimate decision depends on fit rather than exposure.

A Step-by-Step Guide to Choosing the Right ITSM Platform

Choosing the best enterprise IT service management tool is much more than ticking features off a checklist. It must adapt existing processes, integrate with other technology systems, meet required security standards and delivers value without requiring an undue implementation burden. A practical test around four dimensions.

Step 1. IT Maturity & ITIL Alignment Audit

First, document the established workflows your IT team currently completes in your incident management, service request management, change management and asset management processes. Note the approval points, locations where staff are updating a spreadsheet and activities without assigned owners. Assess how the workflows fit with your existing ITIL processes and business requirements. Buying software before you streamline a workflow will simply automate a problem.

Step 2: Map Integration Dependencies

ITSM platforms aren’t a stand-alone offering. Will your platform need to integrate with Slack or MS Teams, HR platforms, monitoring and observability tools, identity platforms, and your current asset database? Examine what APIs are offered and what pre built connectors are available, also what data will be synchronized and the likely need to maintain the integration. Map the flow of data between the two systems and establish if one process (e.g. a new employee onboarding request) will set off provisioning of accounts, equipment and access. Heavy integration will cost more and take longer than you think.

Step 3: Consider SaaS Compared to On-Premises Deployment

It can also be that to reduce infrastructure management cloud-based platforms are more appealing but on-premises or on-site deployments are more acceptable where control or operational requirements are specific to an organization. This ultimately depends on data sovereignty, compliance, and security policies and resources.

NIST SP 800-18 Revision 2 (June 2026) The system planning references that can be part of your system plan are: system purpose; whether selected security controls (including privacy controls) are implemented and the effectiveness of the implementation; and the roles and responsibilities for those managing, supporting, or using the system. ITSM builds upon the knowledge of your cybersecurity supply-chain risk.

Step 4: Assess Total Cost of Ownership Against Time-to-Value

Cost from the subscription fee is only a portion. Combine up the implementation, third-party consultants, customization, integrations, training, the future management and upgrades for total cost of ownership (TCO). Then, determine how long you’ll need to realize real benefits, like faster incident resolution or fewer manual handoffs.

An entry-level can be time-consuming to set-up a platform that is more costly can be better aligned with your existing business processes. Ask for a proof of concept based on real use cases before you buy. Pick the enterprise IT service management tools that address your key issues and provide value at a rate your business can absorb.

Building a Business Case for Your ITSM Investment

When educating the C-suite about your ITSM investment, relate the platform’s features to the impact on business outcomes. CFOs want to see total cost of ownership, potential savings and the impact of manual work. CEOs will expect that improved delivery of IT services will enable their workers to be productive and ensure business resilience. To give them context, compare current rates of incident activity, backlog of requests, persistent issues and hours spent on repeatable tasks to the outcomes they will experience when enterprise IT service management tools are used to reduce your operational risk, prevent process delays and handle higher-value IT work. Identify metrics upfront to measure success.

Conclusion

The first thing that should be done in selecting enterprise ITSM tools is knowing how your business operates. You will have to factor in process mapping, integration needs, security, deployment, and total cost of ownership prior to making any decision. Service Now, BMC Helix, Jira Service Management, Manage Engine Service Desk Plus, Ivanti, and Freshservice solutions should be considered based on your requirements. Eventually, an ITSM tool should be able to serve as a system of record for incidents, assets, service requests, and changes that would enable decision-making. This guide uses the ITIL-based approach and NIST/CISA provided info to help you understand how to make informed decisions about your ITSM solutions.

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This collaboration is based on their previous cooperation concerning EDR/XDR solutions that now extends into enterprise AI governance area. With the advent of generative AI and autonomous AI agents, there arise new challenges for security professionals related to data leakage, prompt injection, and usage of “shadow AI.” Through the implementation of SentinelOne Prompt Security in Lenovo ThinkShield hardware-software ecosystem, along with the Security Services of Lenovo, the alliance is able to offer a unified control plane to enterprises to discover and govern AI interactions.

“Security leaders are being asked to enable AI across the business and answer for where company data goes,” said Melissa K. Smith, SVP, Global Strategic Partnerships and Initiatives at SentinelOne. “SentinelOne Prompt Security gives them visibility into the AI tools in use and control over how data is shared, protecting against data leakage, prompt injection, and AI misuse. Through Lenovo ThinkShield, we are bringing that control to more organizations as they adopt AI.”

Below the Surface: Hardware-Based Governance and In-Moment Prompt Security

Traditionally, enterprise IT teams have dealt with cybersecurity risks by securing network perimeters, endpoints, and cloud workloads from known forms of malware and network intrusions. However, the rapid proliferation of generative AI software and agents has presented non-deterministic risks such as employees inputting proprietary intellectual property or PII information into external AI models or unauthorized access to internal databases through the use of AI.

Also Read: Scaling Productive AI: How Cloudflare’s AI Workspace Platform Redefines Enterprise Artificial Intelligence 

The extended collaboration between SentinelOne and Lenovo provides for the following measures aimed at addressing these operational risks with a multi-layered defense and governance approach:

AI Discovery (Sanctioned & Shadow AI): Automatic discovery of all AI services and software used in enterprise environments to provide full visibility on how the enterprise employees use AI-based software.

Data Loss Prevention (DLP): Blocking sensitive files, source code, and documents from being sent to unauthorized third-party AI services to allow enterprise employees to utilize AI safely.

Policy Enforcement on the Endpoint: Enforcing real-time policies directly on Lenovo hardware beyond traditional endpoint protection to secure AI prompts.

SentinelOne AI Security Stack and Lenovo Global Managed Security Services: The combination of SentinelOne’s AI security stack with Lenovo’s global consulting and management services helps

Strategic Impact on the Cybersecurity and Endpoint Security Industry

Unifying endpoint hardware production with real-time AI prompt security and governance signals a fundamental shift across the Cybersecurity and Endpoint Hardware landscape:

1. The Intersection of Hardware Production and AI Data Governance

Historically, hardware manufacturers would offer physical security measures (such as self-healing BIOS and chip-based encryption) while software producers would be responsible for the data security. By adding SentinelOne Prompt Security to Lenovo ThinkShield, the integrity of hardware is combined with real-time AI data governance. OEMs cannot compete anymore based only on performance and reliability of hardware – now they need to provide “AI-safe” hardware devices with the built-in runtime governance capabilities.

2. From Endpoint Detection (EDR) to Runtime Agent Governance

Once companies advance from simple chatbots powered by AI to self-governing AI agents that have credentials to call API’s independently, regular endpoint detection and response (EDR) solutions reach their capacity. EDR finds the malicious execution of code, but an AI governance solution should understand the meaning and context of natural language prompts and tools. Prompt security features on top of the commercial fleet of PCs become the new standard for endpoint security suites.

3. Addressing “Shadow AI” Visibility Problem

One of the major headaches for Chief Information Security Officers (CISOs) is the absence of oversight of the consumption of AI tools by distributed workforces. An outright ban of AI tools will greatly reduce productivity of employees, but lack of oversight poses compliance risks and IP leaks. Endpoint visibility provides an opportunity for companies to progress from a total ban to a well-managed AI adoption.

Overall Effects on Businesses Operating in the Cybersecurity and IT Sector

The partnership between SentinelOne and Lenovo shows definite operational, competitive, and purchasing trends among enterprise IT buyers, cybersecurity vendors, and PC vendors:

Reducing Barriers to Enterprise AI Security and Adoption: Enterprises that are reluctant to adopt AI technology because of legal and IP concerns have the opportunity to streamline their process of adoption, aware that there is native data loss prevention and auditability within the system.

Disintermediation of Independent Browser-Based AI Prompt Gateways: Software companies that sell independent AI governance software will be disintermediated because enterprises will prefer security platforms incorporated directly into their endpoint management and PC purchase process.

Elevating Managed Security Service Provider (MSSP) Offerings: Managed service providers and IT integrators can package high-margin “AI Security and Governance Audit” tiers by leveraging Lenovo’s managed services ecosystem, unlocking predictable recurring revenue streams.

Conclusion

SentinelOne and Lenovo’s expanded partnership marks a vital milestone in modern endpoint security. By embedding AI prompt governance directly into Lenovo’s global ThinkShield ecosystem, the collaboration bridges the gap between hardware computing and runtime AI protection. For the broader cybersecurity and IT industry, this release confirms that securing the future of work requires making AI governance an ambient, hardware-grounded capability.

The post SentinelOne and Lenovo Extend Collaboration With AI Agent Security Capabilities appeared first on ITDigest.

Also Read: RapidCanvas Secures $29 Million Series B to Scale Managed Enterprise AI Execution Globally 

“Global enterprises need to unlock the full power and potential of every endpoint device they have deployed, whether they be PCs in use among their workforces or advanced machines used by AI developers to shape the future of autonomous business,” said Christy Wyatt, President & CEO, Absolute Security. “Our work with NVIDIA will deliver a needed breakthrough in endpoint management, security, and cyber resilience that will help customers leverage AI without sacrificing needed security and compliance controls.”The collaboration addresses growing enterprise demand for secure AI infrastructure as autonomous agents gain access to applications and business workflows.

Read More: Absolute Security Integrates Autonomous Cyber Resilience into the NVIDIA DGX Station AI Supercomputer

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Keeping up-to-date as-running documentation of an industrial network is tedious, manual work. More often than not, OT documentation doesn’t exist, or the environment has drifted so far it’s of little use to OT teams. Manual assessments take weeks of labor across a myriad of tools, and the compliance artifacts they produce are often still incomplete and inaccurate.

Folio uses the power of Corsha Gatekeepers to capture the identities, connections, and data flows on the OT network, answering what is communicating, when, why, and how. Teams can generate derived hardware lists, connection maps true to the moment, and Microsoft Visio data flow diagrams. That documentation is ready to share across OT, security, and network teams and is designed for risk management and compliance frameworks, including IEC 62443, NERC CIP, and Zero Trust.

Also Read: Spectrum Instrumentation General-purpose digitizers get onboard averaging function

Unlike previous manual approaches, Folio brings together real-time connections, data flows, machine identity, and access intelligence. Rather than building more data-drowning dashboards, Folio produces actionable artifacts that teams can use to assess risk, make real-time decisions, and modernize with confidence.

“Industrial enterprises can’t modernize safely when their operational picture no longer reflects how their operations actually run,” said Anusha Iyer, Founder and CEO of Corsha. “Folio builds on the identity intelligence at the heart of our platform to give security and operational leaders an accurate, current understanding of every machine and every connection, and its purpose in their environment. That means faster recovery when incidents happen, compliance that keeps pace with change, and a clear path to adopting new technologies like robotics and physical AI. We are excited about this use of AI and ML in the Corsha platform to automate the tedious but critical work of day-to-day operations.”

Folio supports three core use cases:

• Day-to-day operations: For OT operators who assess risk, make daily decisions, and respond to incidents, Folio removes the need to manually maintain system and network documentation.
• Continuous compliance: For OT leaders working to clear compliance roadblocks to innovation, such as Authority to Operate (ATO), Zero Trust, and NERC CIP, Folio delivers updated system, connection, and architecture documentation in minutes.
• Accelerated technology adoption: For OT leaders and architects bringing in advanced robotics, physical AI, predictive analytics, and more, Folio enables teams to assess the impact of new industrial capabilities on brownfield environments to speed production deployment.

Key Folio capabilities include:

• Real-time visibility – Uses the Corsha Industrial Identity Security Platform and its Gatekeepers to deliver the most current, as-running view of what’s on the OT network.
• Connection intelligence – Maps connections and data flows, not just inventory, so teams can answer the what, where, when, and why questions needed to secure and modernize their operations.
• Identity core – Builds on the Corsha Platform’s identity-based foundation to monitor and track changes that IP addresses alone can’t reveal, keeping assessments accurate as operations evolve.
• Architecture design – Lets teams design boundaries, zones, and machine groups on a live Connection Canvas that shows data flows, connections, and the segmentation and policies that are live and enforced.
• IEC 62443 native – Speaks the industry-standard language of IEC 62443, from the Connection Canvas through to exported assessment artifacts.
• Visio export ready – Exports accurate operating diagrams to Microsoft Visio so teams can collaborate in the most common OT design format.

With the new Corsha Folio module, organizations can cut the time spent on compliance activities by orders of magnitude, reduce time to recover from security incidents and errors, prevent misconfigurations and downtime with always up-to-date system specifications, and eliminate the cost of manually maintaining operations documentation.

The post Corsha Releases Folio to Forever Replace Manual OT Network and Compliance Documentation appeared first on ITDigest.

In his new position, Serassio will focus on connecting market insights, customer conversations, and industry relationships with Glow’s strategic priorities. His responsibilities will include helping translate feedback from the cybersecurity community into actionable insights that inform the company’s direction and customer engagement.

Reflecting on his career transition, Serassio acknowledged the Lockstep team and community for their support and the opportunities that contributed to his professional development. He also highlighted the importance of relationships built with colleagues, customers, partners, and industry peers throughout his career.

Also Read: Virtuozzo Updates Infrastructure System to Support Flexible Deployment and NVIDIA Integration

The appointment comes as artificial intelligence reshapes enterprise operations and creates new challenges for cybersecurity teams. As organizations adopt AI-powered applications and tools, security professionals face growing demands to understand what is operating across their environments and address potential risks before they develop into incidents.

Glow focuses on endpoint security, with an approach centered on improving visibility and preventing security issues rather than relying solely on detecting and responding to threats after they occur. This shift reflects a broader industry discussion about how traditional security strategies must evolve to address increasingly complex technology environments.

Serassio’s experience working closely with cybersecurity leaders and founders is relevant to this changing landscape. His new role will bring together industry engagement, relationship building, and strategic execution, helping ensure that market perspectives contribute to organizational decision-making.

His move highlights the growing importance of collaboration between security practitioners and technology companies as the industry works to address emerging risks associated with AI adoption. As cybersecurity priorities continue to evolve, translating real-world challenges into practical strategies remains an important consideration for enterprise technology leaders.

The post James Serassio Joins Glow as Head of Strategic Initiatives appeared first on ITDigest.

The platform provides a two-layer solution that enables partners to either use automation multi-tenant administrative management or direct intelligence stream access. Due to the lack of technical restrictions, SOCRadar allows partners to add a turnkey white label threat intelligence platform to their product line or provide the raw telemetry to use in their proprietary products.

Trade-Off Between Customization and Scalability in Managed Security

There was always a problem for MSSPs and enterprise IT providers who were planning to commercialize cyber threat intelligence. While organizations that wanted to create proprietary features based on external data were limited to the use of rigid prepackaged vendor feeds that were not allowing differentiation of the product, those who wanted to use turnkey white label platform had to face heavy back-office administrative tasks based on manual onboarding, licenses issuing, and tenant creation.

Also Read: Arctic Wolf and Veeam Form Strategic Alliance to Integrate Backup Intelligence directly into Security Operations Architecture 

SOCRadar’s dual-layered API framework eliminates these operational roadblocks by combining two distinct functional engines into a single architecture:

Multi-Tenant API: Serves as a two-way automation tool enabling the partners to generate security alerts, control the license distribution, add new client tenants, and update global configurations automatically.

Advanced API: Offers developers and engineers the capability to interact directly with raw cyber threat data without any compression. This raw data helps build custom analysis models, unique platform functionality, and proprietary threat identification processes.

This dual-pronged mechanism gives cybersecurity service providers complete control over their deployment models, whether they opt to white-label SOCRadar’s turnkey platform capabilities or extract raw intelligence to power internal security tools.

Unfiltered Executive Statements

“We’re done making partners choose,” said Huzeyfe Onal, Co-Founder and CEO of SOCRadar. “Our new dual-layer, two-way API suite provides two distinct threat intelligence engagement models to either build it themselves or take it ready-made. For those who want a finished, white-label product, we provide an automated engine that provisions, licenses, and manages tenants at scale. For those who want to build, we open direct access to the raw intelligence that powers SOCRadar. Either way, our partners stop adapting to us and we start adapting to them, which is the way it should be.”

Driving Efficiency Across Global Managed Security Operations

By streamlining how threat intelligence is ingested, branded, and scaled, SOCRadar continues to lower operational overhead for cybersecurity service providers worldwide. The release reinforces the company’s commitment to providing flexible, AI-driven external attack surface management (EASM) and brand protection solutions that adapt to its partners’ evolving business strategies.

The post SOCRadar Debuts Dual-Layered API Suite to Empower Managed Security Service Providers with White-Label and Custom Threat Intelligence Capabilities appeared first on ITDigest.

Three Developments Worth Watching

1. DigitalOcean builds for self-improving AI agents: Managed memory, data services and feedback loops could simplify the development of autonomous applications.
2. NVIDIA and Cisco target AI infrastructure bottlenecks: High-density optical connectivity aims to support larger AI systems with greater efficiency.
3. HighByte and Databricks connect industrial data with AI: Governed, contextualized factory data could help manufacturers move from isolated experiments to operational use cases.

These developments matter because AI progress increasingly depends on what surrounds the model: reliable infrastructure, usable data and the ability to translate insights into action.

5 Technology News Stories

1. DigitalOcean Introduces Agent Learning and Data Services

DigitalOcean has introduced managed services for autonomous AI agents, combining persistent memory, vector data management and continuous feedback on its cloud infrastructure.

The move addresses a practical barrier to agent adoption: developers often need to assemble multiple services to maintain context and improve agent performance. Integrating these capabilities could reduce development complexity and make costs easier to manage, particularly for startups. However, self-improving systems still require evaluation, safeguards and human oversight. Easier deployment will matter most when agents perform reliably in real-world workflows.

2. NVIDIA and Cisco Collaborate on High-Density Optical Modules

NVIDIA and Cisco are developing a high-density, pluggable optical interface designed to connect increasingly large AI infrastructure and GPU clusters.

As AI workloads scale, networking bandwidth, power consumption and heat increasingly constrain data-center design. More efficient optical connectivity could help operators expand computing capacity without proportionally increasing networking overhead. A standardized approach may also simplify deployment across infrastructure ecosystems. The broader lesson is that AI scaling depends on more than faster processors. Connectivity and energy efficiency are becoming equally important considerations in infrastructure investment.

3. Xero Integrates Google Gemini for Financial Analytics

Xero is integrating its accounting intelligence with Google Gemini, allowing small businesses, advisors and bookkeepers to query financial data and generate reports through natural-language prompts in Google Workspace.

The integration could reduce the time small businesses spend switching between accounting dashboards, spreadsheets and documents to understand cash flow or investigate financial trends. It also brings AI closer to everyday decision-making instead of requiring users to learn separate analytics tools. The key test will be whether answers remain accurate, secure and useful enough to support financial decisions without replacing proper verification.

4. Atos and Fortinet Expand Their Global Cybersecurity Partnership

Atos and Fortinet are expanding their partnership into a globally coordinated cybersecurity model for hybrid and multicloud environments, combining security technology with consulting and managed services. The arrangement draws on Atos’s network of 17 security operations centers.

For multinational organizations, a more unified approach could reduce fragmented security policies, inconsistent regional contracts and visibility gaps across cloud environments. It also reflects demand for managed protection as security teams face complex threats and talent shortages. However, vendor consolidation only helps if organizations retain clear oversight, consistent service quality and measurable improvements in threat detection and response.

5. HighByte and Databricks Make Industrial Data More Accessible for AI

HighByte and Databricks are extending their integration to stream contextualized industrial data into the Databricks Data Intelligence Platform, supporting analytics, machine learning and agentic AI applications.

Manufacturers often hold valuable operational data across disconnected systems, making it difficult to use consistently in AI projects. Connecting industrial data with governed analytics infrastructure could reduce custom integration work and help teams apply insights to quality, productivity and maintenance. The challenge remains data quality and governance. AI cannot produce dependable operational decisions when underlying factory data is incomplete, inconsistent or poorly contextualized.

ITDigest Featured Article

Future of Digital Payments: How Fintech Disruption Is Reshaping the Global Financial Ecosystem

Digital payments are evolving through real-time transfers, digital wallets, embedded finance and AI-driven fraud detection. This article examines how these technologies are changing customer expectations, business cash flow and financial inclusion. It also explores persistent challenges, including cross-border friction, security risks, regulation and system integration. Its central argument is that faster payments create value only when businesses combine convenience with reliability, interoperability and customer trust.

ITDigest Weekly Observations

This week’s announcements point to a shift from isolated technology upgrades towards connected systems built for practical use. AI agents need reliable memory and governed data; AI infrastructure needs efficient networking; businesses need financial and operational insights they can act on; and cybersecurity must scale across increasingly complex environments.

The common challenge is execution. Integrations can reduce friction, but they cannot compensate for weak data, poor governance or unclear business objectives. As these technologies mature, the next question is: Which organizations will turn these connected capabilities into measurable productivity gains, and which will remain stuck in implementation?

The post ITDigest Weekly Roundup: Self-Improving AI, Smarter Infrastructure and the Future of Digital Finance appeared first on ITDigest.

As the adoption of Microsoft Copilot and Generative AI workflow becomes increasingly popular among smaller and medium-size companies, MSPs find themselves on a fine line when it comes to providing productive work within the modern workplace environment without being exposed to extreme data leakage, shadow AI and credential risk. The new platform from Proofpoint bridges this gap with multi-tenant management, auto-risk scoring and live DLP in the AI-powered MS 365 workload for MSPs.

“Many organizations are currently considering which AI solutions to deploy. Just as important, however, is which data and communication channels these technologies will interact with. Overly broad permissions, unclear sharing settings or a lack of confidence among employees do not arise because of AI, but its use can amplify their impact. Organizations therefore need to build AI readiness on strong security foundations,” explains Daniel Hofmann, GM & EVP, Proofpoint MSP Platform.

Human-Centric Security Meets Multi-Tenant Automation.

Previously, SMBs have used either native, built-in cloud security tools or a series of disconnected point solutions with limited capability to catch sophisticated, human-fueled threats. Now, with the advent of generative AI copilots (like Microsoft Copilot), there’s added risk. AI copilots build a context from across an entire enterprise tenant, so poorly designed access controls and unreviewed user prompts can give away sensitive IP, HR, or financial information.

Also Read: Atos and Fortinet Establish Global Cybersecurity Partnership to Address Enterprise Security Challenges 

Proofpoint’s new MSP architecture addresses these operational pain points with a dedicated, partner first architecture:

Multi-Tenant AI Risk Visibility: offers managed service providers with a single console that enables them to view prompt activity, access to sensitive data, and risky behaviors of user all at once across all the managed Microsoft 365 tenants.

Automatic DLP Enforcement: Blocks sensitive data such as PII, financial data, and intellectual property from entering any unapproved external AI models or leaking via any internal AI queries within the enterprise.

MSP Workflow Simplification: Combines tenant health management, threat detection, and billing into one platform to lower cost-to-serve for service providers and expedite threat detection and remediation.

Strategic Impact on the Cybersecurity Industry

When you deploy specialized AI governance and threat protection over managed channel platforms, you usher in important structural realignments into the Cybersecurity & Managed Services areas:

1. The Transition from Perimeter Defense to “AI-Contextual” Data Governance.

Legacy cybersecurity efforts concentrated on perimeter protection and blocking malicious files from the outside. Generative AI tools work from the insidegiving users the ability to call upon AI assistance with legitimate prompts, and users having access to internal files. Proofpoint‘s release is the first clear sign of an industry movement toward AI-contextual protection where protection technology is constantly checking users’ identity, the intention behind their prompt, and the sensitivity of the data before responding.

2. Democratizing Enterprise-Grade AI Security for the SMB Segment.

In the past, advanced Data Loss Prevention (DLP) and identity threat detection solutions were accessible mainly to organizations with large enterprise budgets and dedicated Security Operations Center (SOC) teams. By providing AI-focused governance tools through an automated MSP platform, mid-market, and small businesses can now use tools like Microsoft 365 Copilot more securely. This approach enables SMBs to achieve enterprise-level risk management without the need for in-house cybersecurity engineers.

3. Resolving “Shadow AI” and Misconfiguration Vulnerabilities

The primary risk for organizations using Microsoft 365 Copilot is over sharing of data due to old file permissions. If users provide wide access to internal folders, Copilot indexes those files and brings confidential content to unintended internal users. Automatic risk scoring enables MSPs to discover and remediate overshared files before deploying Copilot.

Overall Effects on Businesses Operating in the IT & Cybersecurity Sector.

The raise in Proofpoint’s scale raises the stakes for other managed service providers, security software vendors, and enterprise customers:

Higher Service Margins for MSPs: MSPs can leverage tenants security management via automation and conduct AI risk audits to provide high-margin “AI Readiness and Security” managed service tiers that generate ARR without additional admin FTEs.

Lack of AI Governance Will Hurt Un-Governed Cloud Security Bundles: customers of IT service providers for Standard, non-Governed Cloud Security Bundles that offer email filtering without DLP or AI governance will start leaving them in droves. Business leaders want MSPs that can secure their AI integrations.

Reducing legal and regulatory compliance liabilities Automated enforcement of DLP protection avoids compliance violations like GDPR HIPAA PCI-DSS and reduces the regulatory penalties faced by SMBs and their IT partners.

Conclusion

This Proofpoint platform expansion marks a critical evolution in channel-led cybersecurity. By providing the combination of human-centric threat protection with the automated, AI-based Microsoft 365 AI governance, the platform bridges the gap between software innovation at a fast rate and secure operational execution. To the cybersecurity industry at large, this launch is an indication that the future of enterprise protection is the safe, governed, and scalable adoption of AI for all businesses.

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