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Using Technology to Supplement Human Action
Enterprise Security Magazine | Friday, December 16, 2022
Although technology plays a significant role in the efficient administration of a business, people continue to be essential to long-term success.
FREMONT, CA: The importance of people in businesses is frequently undervalued among the tremendous advancements in technology. Although technology plays a significant role in the efficient administration of a company, people continue to be essential to long-term success. Using cutting-edge technologies to give people information to make smarter, more informed decisions is critical as organisations aim to boost resilience, agility, and innovation.
Employees still play a big part in logistics, for instance, in the supply chain industry. Despite the rapid advancement of automation, businesses still require workers in warehouses for a variety of tasks, including pick-and-pack, handling advanced shipment notices, dispatch, customer interaction, and brand loyalty building. They are still necessary for the first and last mile. Organisations see the highest performance increases in these areas by implementing technology like artificial intelligence (AI) and machine learning (ML).
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These tools support subject-matter specialists' years, if not decades, experience. Through the use of prescriptive insights that significantly enhance results and boost productivity, they enable people to become more proactive. This combination of technology and people substitutes the loss of tribal wisdom while improving the quality and scope of every choice.
This relates to the expertise gained by seasoned workers familiar with the quirks of particular regions, markets, or clients. This information might follow them into retirement, resulting in missed opportunities or unanticipated challenges.
For instance, despite the timings listed on the schedule, a long-time manager in a warehouse may be aware that a certain delivery always arrives a little early. If they depart and take that information with them, there may be a problem when the delivery arrives early the following week, and the loading dock is not prepared, leading to delays.
Utilising AI, ML, and prescriptive insights can assist organisations in avoiding the negative effects of such deviations. Based on previous deliveries, the new manager can receive a weekly reminder to be prepared early for this specific delivery. Overall, leveraging technology to boost the skills of subject-matter specialists results in significantly increased operational efficiency and ensures resilience in the face of a personnel change.
Optimising Resource-allocation
Demand sensing, which has historically been a highly complex operation, is a prime example of how these technologies might positively influence. Retailers with multiple locations may be caught off guard by the effectiveness of product promotions in certain areas if they need help to sense changing demand. Take Spar, a significant food retailer in Austria, as an example. Spar discovered it lacked the data necessary to enable proper store inventory control at the shelf level to increase on-shelf availability. Because they were forced to rely on erroneous, out-of-date, and reactive data calculated by a central office, stores risked running out of inventory.
To give managers the necessary control, Spar wanted an end-to-end resource planning and point-of-sale system. It implemented a unified data platform to achieve this goal, providing shop managers with a thorough and precise end-to-end picture of their sales, inventory orders, and delivery. It was possible to accomplish this on a large scale, but the developments continued. Using embedded AI and ML, the company optimised replenishment by real-time sensing of 800 promos in each of its 1,500 locations. Forecasting demand has been greatly improved as a result.
Another illustration is Paltac, a significant Japanese cosmetics wholesaler, which increased labour productivity by shifting 50,000 goods from 1,000 manufacturers to 400 retailers running 50,000 outlets. This was part of the company's digital transformation effort, which was undoubtedly a huge task.
The business created its in-store assistance application using a data platform with AI and ML, which is effectively the first step in the digital journey. Project managers may assign tasks and communicate with team members on the go using the tool, which is accessible as a desktop and mobile app. Team members can also communicate promotional ideas and record their findings.
Paltac has experienced increased productivity throughout its supply chain as a result. This has allowed for a unified workflow with real-time, accurate information, which has helped the company increase revenues, decrease operating costs, and achieve an unheard-of, on-time, in-full (OTIF) metric of 99.999pc. A site will offer producers and merchants, the two ends of the supply chain, information as the system evolves, and the company will integrate AI to automate human assignments.
In industries like retail and supply chain, the use of technology to supplement human activity is already having a significant influence, but its introduction requires careful handling and constant attention to change management. Employees need to comprehend how technology will increase their productivity and enable them to perform more intelligently.
No matter the sector, harnessing data to get real-time visibility and make better-educated decisions is fundamental to empowering individuals. Organisations must gather data from all business areas to achieve a sense and respond solution, with human intervention guided by prescriptive insights. By utilising a smart data fabric architecture, organisations may get the predictive and prescriptive insights they need to deal with demand spikes, disruptions, and limits.
By integrating and normalising various forms of data and utilising embedded AI and ML, this sort of data architecture, supported by a single data platform, aids businesses in overcoming the traditional lack of end-to-end visibility.
In essence, four factors–see, understand, optimise, and act—are crucial for improving human decision-making inside organisations. End-to-end visibility comes first. The insight driven by data is the second. The third is the orchestration and forecast from beginning to conclusion. Additionally, the achievement of end-to-end coordinated decision-making results in the "act" component, which transforms the productivity of the entire company.
Business leaders will gain from implementing this strategy through a single, unified data management platform by having a workforce that is exponentially more productive and responsive.
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Visibility begins with knowing which device generated a query and where that request traveled. Internet-only inspection can miss traffic that remains inside the enterprise, particularly in distributed networks where applications depend on internal DNS records. Useful protection needs coverage at the point where queries originate, supported by searchable logging that gives security teams enough context to investigate suspicious behavior. DNS data should also feed existing security tools rather than create another isolated console. Integration with SIEM platforms and established security controls can shorten the path from detection to investigation.
Hybrid infrastructure creates a separate purchasing problem. Enterprises rarely operate on a clean network built around one architecture. Legacy DNS services may remain in place while workloads spread across data centers and public clouds. Replacing that infrastructure can introduce migration risk and delay security improvements. A practical DNS security platform should be able to sit over existing environments, centralize policy and extend control without forcing an immediate rebuild. API access also matters because repetitive DNS administration becomes costly when changes across large networks still depend on manual intervention.
“Access Quality layers centralized DNS control over existing infrastructure without forcing buyers into a wholesale replacement.”
Availability deserves equal scrutiny, as DNS protection cannot become another point of failure. Traffic surges and denial-of-service attacks can disrupt access even when the application infrastructure remains healthy. Buyers should examine how DNS security handles sudden demand, distributed environments and malicious traffic while preserving response availability. Policy enforcement also needs to remain consistent as applications move between locations. A security model that works only in one cloud or inside the corporate network leaves the enterprise managing different rules across the same service path.
Regional deployment adds another layer of complexity. Large organizations may need local technical support, training for internal teams and deployment choices that reflect existing network designs. The quality of implementation matters here as much as the underlying technology. Centralized control has limited value if internal teams cannot maintain policies or investigate events once the initial project ends.
Access Quality fits this buying logic through BlueCat-based DDI and DNS security deployments that combine DNS control with DHCP, IP address management and native protection. BlueCat DNS Edge can inspect internal and external DNS activity while forwarding logs into SIEM environments and working alongside Cisco Umbrella.
It layers centralized DNS control over existing infrastructure without forcing buyers into a wholesale replacement. Its use of BlueCat Micetro DDI and Integrity DDI also supports hybrid and multi-cloud management, while RESTful API integration helps reduce manual administration. For enterprises that need broader DNS visibility without rebuilding the network underneath it, that combination merits close consideration. ...Read more
Identity theft has shifted from isolated financial fraud to a broad digital risk affecting employees, families and institutions. Criminal networks now deploy AI-driven impersonation, automated payment scams and large-scale data harvesting to exploit individuals at speed. For executives responsible for selecting identity and privacy protection providers, the issue extends beyond offering a benefit. It involves safeguarding workforce well-being, reducing reputational exposure and reinforcing institutional trust. Boards increasingly expect leadership teams to demonstrate that identity protection programs are structured, measurable and aligned with broader risk management priorities.
The most credible providers demonstrate depth across the full lifecycle of identity risk. Protection must begin before a loss occurs, through continuous monitoring across credit activity, transactions, dark web sources and emerging scam channels such as email, text and device notifications. Effective programs extend beyond detection alerts. They guide individuals in interpreting threats, provide real-time assistance and assume responsibility for restoring identity when fraud occurs. Dedicated case management, clear ownership of recovery and coverage for eligible scam losses signal whether a provider can meaningfully reduce harm rather than simply notify users. Clear communication during incidents also strengthens confidence among employees and customers who expect immediate clarity rather than fragmented support.
Prevention requires education delivered before the moment of vulnerability. Fraud often succeeds by creating urgency and fear, prompting individuals to act without verification. Ongoing awareness initiatives, timely alerts and targeted guidance help shift behavior in advance. Tools that allow individuals to manage their digital footprint and request removal of exposed data from broker sources further reduce repeat targeting. Organizations also benefit from vendors that address disproportionate fraud exposure among seniors, families and vulnerable populations through focused knowledge centers and accessible resources. Prevention becomes more credible when it is continuous rather than episodic and when individuals receive practical next steps instead of abstract warnings.
Enterprise adoption depends on simplicity and adaptability. Employers and financial institutions face constraints around implementation, adoption and integration within existing platforms. Providers that streamline onboarding, offer configurable plans and embed protection directly into digital environments support higher engagement and clearer reporting. Large enterprises require evidence of scale, sustained innovation and the ability to anticipate shifts in identity itself as biometric authentication and device-based credentials become more prevalent. Vendors must demonstrate that their roadmap keeps pace with changes in how identity is defined and exploited.
Allstate Identity Protection aligns closely with these expectations. Built on its nearly two decades experience in the identity protection market and supported by a longstanding national brand associated with protection, it positions trust at the center of its approach. Its model spans education, detection, prevention and restoration, combining credit, transaction and scam monitoring with proactive device-level scam detection and personal data removal capabilities. The company assigns certified specialists to oversee each restoration case, ensuring continuity of support until resolution. It also provides eligible scam loss reimbursement beyond what many financial institutions offer and partners with established cybersecurity and family digital safety providers to strengthen its platform. Serving a significant share of Fortune 500 clients while remaining accessible as an employer benefit, it demonstrates both scale and adaptability. For organizations aiming to embed comprehensive identity and privacy protection within employee and customer ecosystems, it represents a disciplined and forward-looking choice. ...Read more
In an increasingly interconnected world, businesses face a growing number of cybersecurity threats that continue to evolve in complexity and scale. Traditional network defense systems, while effective to a certain extent, often struggle to keep pace with the sophisticated tactics employed by cybercriminals. In response to this, AI-powered firewall solutions are gaining traction as a cutting-edge method to enhance cybersecurity efforts.
These intelligent systems leverage machine learning and artificial intelligence to detect, analyze, and mitigate threats in real-time. By automating threat detection and response, AI firewalls offer businesses a more dynamic, proactive approach to security, addressing some of the limitations inherent in traditional security frameworks.
The Power of AI in Firewall Technology
AI-driven firewalls set themselves apart from traditional ones by processing incoming network traffic through data analysis, predictive modeling, and advanced algorithms for decision-making. Traditional firewalls apply a set of rule-based patterns to detect malicious activity, often becoming unprotected against new, unknown threats.
AI firewalls, in contrast, continuously learn from historical data and establish correlations between user behaviors and network traffic patterns that can be used to identify suspicious, anomalous activities, which could either be deviations from the norm. It gives AI firewalls the ability to detect zero-day attacks, previously unknown vulnerabilities, and emerging threats that otherwise might have escaped scrutiny.
AI firewalls are enabled with real-time decision-making capabilities to counterattack potential threats immediately. Firewalls, based on the nature of the attack detected-whether it is a DDoS (Distributed Denial of Service) attack, a malware injection, or an unauthorized access attempt- attempt to adjust their set of precautions dynamically. These properties serve to make AI firewalls correct and fast in their decision-making, which leads to a minimization of incidences of false positives and negatives.
Another key consideration in favor of AI firewalls is scalability. As an organization grows and the network becomes more complex, these firewalls can change and scale in response to the increased traffic, new endpoints, and added security roles. Meanwhile, the traditional firewall has a drawback of requiring manual updates to rules and configurations, which can become tedious and time-consuming as the actual network expands. The AI firewalls, on the other hand, are continually refining the rules and strategies through their own initiatives to ensure security is guaranteed as the organization matures.
The Efficiency and Reduced Costs of Operations
Aside from these advanced means of threat detection, operational efficiency is also where AI firewalls stand out. Traditional security measures require intensive human involvement to configure, monitor, and manage. Security teams need to update firewall rules regularly and check for potential incidents and possible unreported vulnerabilities, which exhaust human resources. AI firewalls reduce such work to a minimum because most are automated, therefore freeing up cybersecurity professionals to partake in high-level strategic work.
Conversely, AI firewalls greatly minimize operational costs through less manual intervention. They can automatically perform routine tasks, including filtering traffic and ranking threats, thereby cutting down on labor costs and human fallibility. Businesses mitigate some of the effects of security compromises by applying automated responses to some attacks; otherwise, the repercussions would result in costly downtimes, reputational degradation, and legal accountability.
AI firewalls greatly facilitate operational efficiency through the rapid identification and elimination of threats. This proactive approach to cybersecurity affords companies excellent network uptime and stability and, hence, productivity protection from operational interruptions. In the finance or healthcare industries, where data safeguarding is paramount, a proactive defensive mechanism guarantees compliance with regulations and protection for clients' sensitive information.
Integrating AI Firewalls within Existing Security Infrastructure
Integration of AI firewall solutions into the existing structure of an organization’s security infrastructure poses several challenges in terms of due diligence and feasibility. Such concern requires an extra look at how these AI systems will work in concert alongside traditional firewalls, intrusion detection systems, and other extant measures. Ideally, AI firewalls will complement already existing solutions by improving their capabilities instead of completely replacing them.
One of the significant issues surrounding the implementation of AI firewalls is the assurance of seamless communication between different security components. A good integration will allow the business to reap the full benefits of AI firewalls' learning capabilities without interrupting other established protocols. Most organizations adopt partial implementations of the AI firewall, essentially starting from the network's most critical parts and then expanding outwards.
For the successful deployment of AI firewalls, there must be a significant investment in further training of cybersecurity practitioners and experts. These will require the acquisition of skills in interpreting data provided by the AI, effective handling of alerts, and optimization of algorithm performance. This way, the company will be in a position to enjoy the full range of benefits afforded by such an advanced system.
In the long run, with the advancement of AI technology, AI firewalls will be a linchpin in comprehensive strategies for safeguarding against cyber threats by proactively predicting threats, managing networks dynamically, and cutting overall costs. As a result, companies adopting an AI firewall into their security infrastructure will build a more resilient and responsive countermeasure for the protection of data and assets in an arduous digital arena. ...Read more
Cybersecurity leaders no longer evaluate multifactor authentication as a narrow login control. It now sits at the center of trust because the network perimeter has been replaced by cloud applications, remote access, mobile users and third-party services. Attackers have adapted. Rather than defeating infrastructure directly, they target the human identity layer through phishing, fake websites, credential reuse, session interception and social engineering. AI has sharpened deception, weakening legacy assumptions about passwords, one-time codes and user vigilance.
Traditional MFA can reduce some exposure, but it often preserves the weakness it is meant to protect. A password remains in the path, a user still has to recognize a fraudulent prompt, a code may still be entered into a hostile session and the burden of correctness often sits with the individual. For executives, this is not just a security design problem. It becomes a cost, productivity and confidence problem. Help desks carry reset volume, employees navigate repeated prompts, customers abandon frustrating processes and fraud teams absorb losses when authentication stops at login but fails to control sensitive actions after access is granted.
The stronger path removes static credentials from daily use rather than hiding them behind more steps. It should make trust mutual, so the service proves itself to the user before the user approves the session. It should also extend beyond login, because access to payroll, funds transfer, privileged systems or sensitive records requires authorization tied to the verified person, not just an earlier sign-in. Biometric confirmation, device trust, cryptographic validation and context-aware checks matter most when they reduce the chance that a stolen credential, copied website or compromised session can become real damage.
Adoption depends just as much on usability. Security teams have spent years asking users to remember, rotate, reset and protect secrets while interpreting security cues under pressure. That model does not scale across banking customers, public-sector users, field employees, shared workstations, legacy applications and VPN access. The right approach should simplify the act of proving identity, accommodate users with different levels of digital confidence and integrate across environments that cannot all be rebuilt. Simplicity is not softness. It is the discipline of reducing unnecessary steps while preserving proof, control and auditability.
Executives should also look for coverage that matches enterprise reality. A solution that works only for new cloud applications can leave exposed systems behind. One that requires broad redesign can slow adoption. One that replaces a single password burden with multiple disconnected authentication paths can dilute governance. The benchmark is a consistent identity experience across cloud, desktop, VPN, legacy, shared and constrained environments, backed by implementation support that lets security leaders test, train and expand without disrupting users.
PasswordFree© emerges as the premier choice for organizations that want MFA to move from layered passwords toward true password elimination. Its differentiator is full duplex authentication, in which the service validates itself to the user before the user confirms identity through a matched image, short code and biometric approval. That design addresses phishing, imposter websites and one-way code entry. Its website scope reinforces the fit through passwordless authentication, Windows Hello extension and coverage across cloud, desktop, VPN, legacy, shared and airgapped systems. For buyers prioritizing trust, broad reach and user simplicity, PasswordFree© offers the clearest path forward. ...Read more
