Agentic AI in Healthcare: Can AI Agents Manage Clinical Workflows? Healthcare organizations are increasingly exploring artificial intelligence to improve patient care, reduce administrative workloads, and make clinical operations more efficient. The next major development is agentic AI—AI systems capable of reasoning, planning, making decisions, and taking actions with limited human intervention. This raises an important question: Can AI agents actually manage clinical workflows? Unlike traditional AI tools that respond to individual prompts or analyze specific datasets, agentic AI can work toward defined goals by coordinating multiple tasks. In healthcare, this could allow AI agents to support physicians, nurses, administrators, and patients across complex clinical processes. What Is Agentic AI in Healthcare? Agentic AI refers to autonomous or semi-autonomous AI systems that can understand objectives, determine the steps required to achieve them, use connected tools, and adapt based on new information. For example, an AI agent supporting a clinical workflow could review a patient's medical record, identify relevant information, prepare a summary for a physician, schedule a follow-up appointment, send appropriate reminders, and monitor whether required actions have been completed. Rather than simply providing information, the agent can help coordinate the workflow from beginning to end. How AI Agents Could Manage Clinical Workflows Clinical environments involve numerous repetitive and interconnected activities. Agentic AI could potentially assist with several of these processes. 1. Patient Intake and Triage AI agents could collect patient information before an appointment, analyze symptoms and medical history, and organize relevant information for clinical staff. In certain controlled scenarios, agents could help prioritize cases based on predefined clinical protocols. 2. Clinical Documentation Documentation is one of the most time-consuming responsibilities for healthcare professionals. AI agents can assist by converting conversations into structured clinical notes, identifying important information, and preparing documentation for physician review. 3. Care Coordination Patients often interact with multiple healthcare providers, departments, laboratories, and pharmacies. An AI agent could coordinate appointments, follow-ups, referrals, and notifications while keeping relevant stakeholders informed. 4. Patient Follow-Up After treatment or discharge, AI agents could monitor scheduled follow-ups, communicate reminders, collect patient-reported information, and flag situations that may require human attention. 5. Administrative Workflows Beyond direct clinical activities, agentic AI could automate insurance verification, appointment scheduling, referral management, prior-authorization workflows, and other administrative processes. Benefits for Healthcare Organizations The adoption of agentic AI could deliver several potential benefits. Automating repetitive workflows may allow clinicians to spend more time on patient-facing activities. AI agents could also help reduce administrative burdens, improve workflow consistency, and accelerate access to relevant information. Another advantage is 24/7 workflow support. Unlike human teams that operate within scheduled hours, AI systems can continuously monitor tasks and identify incomplete or delayed processes. However, the value of agentic AI will depend heavily on how effectively it integrates with existing electronic health records (EHRs), clinical applications, and organizational systems. Challenges and Risks Healthcare is a high-stakes environment, making autonomous AI significantly more complex than agentic systems used in lower-risk industries. Patient safety, data privacy, cybersecurity, regulatory compliance, and AI reliability are major concerns. An AI agent making an incorrect decision could potentially have serious consequences. For this reason, healthcare organizations are likely to favor human-in-the-loop models, where AI agents can execute routine tasks but escalate important clinical decisions to qualified professionals. Strong governance will also be necessary. Organizations must establish clear permissions, audit trails, access controls, validation processes, and accountability mechanisms. The Future of Agentic AI in Healthcare Agentic AI is unlikely to completely replace clinicians. Instead, its greatest potential may come from acting as a digital workflow partner that manages routine coordination while healthcare professionals retain control over critical decisions. As AI agents become more capable and healthcare technology becomes increasingly interconnected, organizations could move from isolated AI applications toward intelligent systems capable of coordinating entire workflows. The key question is therefore not whether AI agents can manage clinical workflows, but how much autonomy healthcare organizations should safely give them. With appropriate governance, human oversight, and secure integration, agentic AI could become an important component of the next generation of healthcare operations. Read More: https://thehealthco.info/

Agentic Finance: Can AI Agents Execute Financial Transactions? Artificial intelligence is moving beyond chatbots and recommendation engines into a new phase known as agentic AI. Unlike traditional AI systems that primarily analyze information or respond to prompts, AI agents can plan tasks, make decisions, interact with systems, and take actions with limited human intervention. In financial services, this evolution is giving rise to a new concept: agentic finance. Agentic finance refers to the use of autonomous or semi-autonomous AI agents to perform financial activities such as managing payments, monitoring accounts, optimizing cash flow, executing trades, and potentially initiating financial transactions. While the technology could significantly improve efficiency, it also raises important questions about security, authorization, accountability, and regulatory oversight. How AI Agents Could Execute Financial Transactions An AI agent operating in a financial environment could be connected to banking platforms, payment systems, accounting software, or investment applications through secure APIs. Based on predefined rules, user instructions, and real-time data, the agent could determine when an action should be taken. For example, a business could authorize an AI agent to monitor supplier invoices. Once an invoice is verified against approved records, the agent could initiate a payment automatically. Similarly, an agent managing corporate cash could identify excess funds and recommend or execute transfers between approved accounts according to predefined policies. In personal finance, an agent could potentially monitor recurring bills, identify unusual charges, move money between accounts, or schedule payments while staying within limits established by the customer. The Benefits of Agentic Finance The biggest advantage of agentic finance is automation. Financial teams spend significant time performing repetitive processes such as reconciliation, payment processing, fraud monitoring, and reporting. AI agents could handle many of these tasks continuously, reducing manual workloads and operational costs. AI agents could also make financial operations more responsive. Instead of waiting for employees to review transactions, an agent could analyze data in real time and react to changing conditions. This could improve cash-flow management, reduce payment delays, and help organizations identify potential fraud or financial anomalies faster. Another benefit is personalization. AI agents could use an individual's financial goals, transaction history, and preferences to provide more tailored financial management and recommendations. Security and Trust Remain Major Challenges Giving AI agents the ability to execute financial transactions introduces substantial risks. A poorly configured agent could send money to the wrong recipient, approve an unauthorized transaction, or make an incorrect decision based on inaccurate information. Cybersecurity is another major concern. If an AI agent's credentials, API access, or underlying systems are compromised, attackers could potentially use the agent to conduct unauthorized transactions. For this reason, financial institutions will need strong controls around authentication, authorization, transaction limits, monitoring, and human oversight. High-value or unusual transactions may still require explicit human approval. What About Regulation? Regulators will also play an important role in determining how agentic finance develops. Financial transactions are subject to strict requirements involving consumer protection, fraud prevention, anti-money-laundering controls, data privacy, and accountability. Organizations using AI agents will need to establish clear responsibility for decisions made by autonomous systems. Audit trails, explainability, approval workflows, and transparent governance will become increasingly important. The Future of Agentic Finance AI agents are unlikely to completely replace humans in financial decision-making in the near term. Instead, the industry is likely to move toward human-supervised autonomy, where agents perform routine and low-risk transactions while humans retain control over sensitive financial decisions. As AI, APIs, digital payments, and financial infrastructure continue to mature, agentic finance could transform how money moves through businesses and financial institutions. The central question is no longer whether AI can execute financial transactions—it is whether organizations can build the security, governance, and trust frameworks required to let it do so safely. Read More: https://thefintech.info/

Keeper Security Names Jessica Krowel and Bill Grabner to Lead North American Sector Sales Keeper Security, the leading zero-trust and zero-knowledge identity security platform, announced the appointment of Jessica Krowel as Senior Vice President of North America Sales, Private Sector, and Bill Grabner as Senior Vice President, Public Sector. Both executives will support Tim Strickland, Chief Revenue Officer, as Keeper continues to strengthen and scale its go-to-market leadership. These key talent acquisitions come on the heels of Gartner® recognizing Keeper as the second fastest-growing competitor in its Market Share Analysis: Security Software, Worldwide, 2025 report. New Go-to-Market Leadership Jessica Krowel brings almost 20 years of go-to-market leadership in identity and access management. She spent 14 years at CyberArk, rising through the ranks to Global Vice President of Inside Sales and Chief of Staff to the Go-to-Market (GTM) organization. Most recently, she served as Vice President of Global Sales Development at Delinea. Bill Grabner brings more than two decades of federal and public sector sales leadership. Most recently, he served as Senior Vice President and General Manager at JMA Wireless, with prior leadership roles at Ribbon Communications, Cisco and BroadSoft. ABM Insights: Optimove Announced the Introduction of the New OptiGenie Krowel and Grabner will support and scale Keeper’s GTM teams across key regions to address demand across: Midmarket organizations Large-scale enterprises Federal organizations Accelerating Keeper’s Growth Last year, Keeper grew its revenue 53.4% in 2025, more than three times the security software market’s overall average of 15.5%, ranking second only to Google in Gartner’s analysis. The $111 billion worldwide security software market grew steadily last year, and Gartner attributed the top performers’ growth in part to platform consolidation and organizations replacing fragmented point solutions with unified platforms. “The cybersecurity market is seeing an unprecedented inflection point with the advent and widespread adoption of AI technologies,” said Tim Strickland, Chief Revenue Officer of Keeper Security. “With Jessica and Bill onboard, Keeper is poised to continue accelerating its rocketing growth as organizations seek identity security solutions that harness the power of AI to protect against existing human risks and emerging agentic AI threats.” Read More: https://theabm.info/keeper-security-names-jessica-krowel-and-bill-grabner-to-lead-north-american-sector-sales

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If an account is verified under another person's identity, the actual operator may not correspond with the information originally submitted. Businesses should therefore understand KYC before deciding how to create, own, and manage a cryptocurrency account. What should a business do before using a verified cryptocurrency account? Before considering Buy Verified Binance Accounts, a business should determine who should own the account, which account structure is appropriate, and whether the proposed arrangement complies with Binance's current requirements. The business should review verification procedures, security controls, privacy considerations, and applicable jurisdictional obligations. It should not rely solely on seller claims such as “fully verified,” “permanent,” or “guaranteed.” Where legal, tax, accounting, or regulatory questions arise, professional advice may be appropriate. 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NeXasure and Atsign Partner to Strengthen Cyber Resilience NeXasure, a pioneering provider of AI-driven cybersecurity managed detection and response solutions with advisory services, and Atsign, the innovative creator of a privacy-by-design networking platform, announced the completion of bilateral marketing and reseller agreements that will help organizations reduce exposed infrastructure, strengthen cyber resilience, and secure both new and existing connected systems. The partnership brings together two complementary technology philosophies: NeXasure’s proactive, agentic AI approach to cyber resilience, which uses a true agentic AI “brain” with a dynamic ontology that accurately detects and remediates cyber threats in seconds instead of hours to days. The Atsign platform, the cryptographic identity and secure communications foundation behind NoPorts and Atsign-enabled applications. The Atsign platform enables the development of secure connected systems without exposed infrastructure. Infotech Insights: Cahill Names Kelly Graves Chief AI Strategy and Innovation Officer Combining AI-Driven Defense With Privacy-First Networking NeXasure Defend leverages Frostbow from SKADI Cyber Defense, a synthetic and agentic AI solution deployed to detect, analyze, and respond to threats in real time. Atsign eliminates entire classes of attack vectors by ensuring that no data is exposed without explicit permission. The platform removes reliance on: Open ports Static IP addresses Vulnerable network configurations Together, the combined solution portfolio offers organizations a comprehensive, privacy-first cybersecurity posture, spanning access, network architecture, and active threat mitigation end-to-end. “This is a significant step forward in our mission to deliver holistic, AI-powered cybersecurity solutions,” said Rick McElroy, Chief Executive Officer of NeXasure. “Atsign solutions eliminate the foundational vulnerabilities that attackers routinely exploit — open ports, exposed services, and discoverable infrastructure. Combined with NeXasure Defend’s real-time AI threat intelligence and our Advisory Services team, we are giving our clients an unprecedented level of protection that is both proactive and architecturally sound.” Read More: https://theinfotech.info/nexasure-and-atsign-partner-to-strengthen-cyber-resilience

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SafeVCCPro may appear in research into payment-related services, but customers should independently verify its current offerings, terms, security practices, and suitability For businesses preparing for 2044, the strongest payment strategy is built around legitimate ownership, accurate information, strong security, transparent services, and compliance with the latest platform requirements.

Remote Patient Monitoring: Transforming Healthcare Through Connected Care Remote Patient Monitoring (RPM) is becoming an important part of modern healthcare as providers increasingly use connected technologies to monitor patients outside traditional clinical settings. By collecting and transmitting health information from patients at home or other locations, RPM enables healthcare professionals to track changes in patient health, identify potential risks earlier, and support more continuous care. What Is Remote Patient Monitoring? Remote Patient Monitoring refers to the use of digital devices and technologies to collect patient health data outside a hospital or clinic and securely share that information with healthcare providers. Devices can include blood pressure monitors, glucose meters, pulse oximeters, wearable fitness trackers, digital thermometers, and connected cardiac monitoring systems. The collected information can provide clinicians with regular insights into a patient's condition. Instead of relying only on periodic appointments, healthcare teams can use ongoing data to make more informed decisions and adjust treatment when necessary. How Remote Patient Monitoring Works A typical RPM system combines connected medical devices, software platforms, communication networks, and clinical workflows. A patient uses a monitoring device to measure a specific health indicator, such as blood pressure or blood glucose. The information is then transmitted digitally to a secure platform where healthcare professionals can review it. Many modern RPM platforms can analyze incoming data and generate alerts when measurements move outside predefined thresholds. These alerts can help clinicians prioritize patients who may require immediate attention. For example, a patient with hypertension can monitor blood pressure at home. If several readings indicate a significant increase, the healthcare team can contact the patient and determine whether medication, lifestyle changes, or an in-person evaluation is required. Benefits for Patients and Providers One of the major advantages of RPM is its ability to extend healthcare beyond conventional clinical environments. Patients can receive monitoring while remaining at home, which can improve convenience and reduce unnecessary hospital or clinic visits. RPM can be particularly valuable for people managing chronic conditions such as diabetes, hypertension, heart disease, and respiratory illnesses. Continuous or frequent monitoring can help healthcare professionals identify changes before they become more serious. For providers, RPM can support data-driven decision-making and improve visibility into patient health between appointments. It may also contribute to better care coordination by allowing multiple members of a healthcare team to access relevant patient information. The Role of AI and Connected Devices Artificial intelligence and machine learning are adding new capabilities to remote monitoring platforms. AI-powered systems can analyze large volumes of patient data, identify unusual patterns, and help prioritize alerts for clinical review. Wearable devices and Internet of Medical Things (IoMT) technologies are also expanding the range of information that can be collected remotely. Continuous measurements can provide a more detailed picture of patient health than occasional manual readings. However, AI should complement rather than replace clinical judgment. Healthcare professionals remain essential for interpreting patient data, understanding individual circumstances, and making treatment decisions. Challenges and Considerations Despite its potential, RPM adoption comes with several challenges. Healthcare organizations must address data privacy, cybersecurity, device interoperability, and integration with electronic health records. Reliable connectivity and easy-to-use devices are also important, particularly for older patients or individuals with limited digital experience. Healthcare providers must additionally establish clear processes for responding to alerts. An effective RPM program requires not only technology but also appropriate clinical workflows and trained staff. The Future of Remote Patient Monitoring Remote Patient Monitoring is expected to remain an important component of connected healthcare. As wearable devices, AI analytics, cloud platforms, and digital health technologies continue to develop, RPM systems could become increasingly personalized and predictive. The future of RPM will likely focus on moving healthcare from occasional, reactive interactions toward continuous and proactive care. By combining real-time patient data with clinical expertise, remote monitoring can help healthcare organizations deliver more accessible, personalized, and efficient care while enabling patients to take a more active role in managing their health. Read More: https://thehealthco.info/