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Crafting the Future with AI, Cloud and Operational Excellence
I have been in the technology field for more than 25 years, working in various industries such as e-commerce, payments, fintech and healthcare.
By
Applied Technology Review | Wednesday, March 11, 2026
I have been in the technology field for more than 25 years, working in various industries such as e-commerce, payments, fintech and healthcare. Before joining Anywhere, I was the Managing Director of Architecture for Evernorth, a division of Cigna. I joined Anywhere Real Estate three years ago to lead the strategic direction and execution of enterprise architecture, software engineering, operations and application reliability.
Challenges while Ensuring System Consistency
Ensuring system consistency as enterprise systems increasingly integrate AI, machine learning (ML) and automation presents several challenges. One major issue is maintaining data quality and consistency, as inaccurate or outdated data can lead to unreliable outputs and inconsistent system behavior. Another challenge is model drift, where AI models become less accurate over time, resulting in inconsistencies in system performance. Integrating AI and ML into existing systems can also be complex, introducing potential inconsistencies. Scalability is a concern, as AI and ML models must scale effectively without compromising performance or consistency.
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To mitigate these risks, Anywhere uses open-source technology to build AI Foundational Services, allowing teams to access and switch different LLMs using the same service, ensuring consistency. Our service tracks model spends and usage, offering early observability on use cases, reducing uncertainty about AI costs. Additionally, our repeatable architecture for chat features ensures consistent deployment and reduces the need for custom solutions.
Best Practices for Balancing Speed with Reliability
Firstly, building the right culture is crucial. Our technology organization principle, reiterated at each meeting, is that "Craftsmanship and Quality are non-negotiable." This principle establishes a team focus on reliability.
Secondly, we automate our testing processes. We set annual goals for unit and functional testing automation and review these metrics monthly to reduce testing cycle times.
Thirdly, we utilize Pipeline and Infrastructure as Code (IaC) to speed up environment setup and application builds, which we consider essential for maintaining speed.
Additionally, we handle code quality and vulnerability by integrating quality and vulnerability scans into our repositories and setting remediation goals. This approach helps reduce downstream functional and security issues.
We also focus on the consolidation of our development ecosystems. Having grown through acquisitions, we had multiple development environments. By consolidating these environments, such as repositories, we reduce the number of pipelines needed.
Lastly, we are committed to continuous modernization. While some best practices may not apply to older applications, we are on a continuous journey to modernize our applications to be cloud-first, enabling them to leverage the aforementioned practices.
Strategies for Maintaining Operational Resilience in Distributed Architectures
The most effective strategies for maintaining operational resilience in distributed architectures, particularly when facing unexpected traffic spikes or network failures, involve a combination of proactive and reactive measures.
“Organizations should invest in these technologies now, build a culture of continuous learning and foster collaboration across departments to integrate these advancements effectively.”
ombination of proactive and reactive measures. Proactively, we design our systems to be micro or modular, ensuring that a failure in one service or component does not bring down the entire ecosystem. We focus on building or modernizing to cloud-native systems with automatic scalability, redundancy and failover capabilities to ensure backup systems are in place in case of failures. Additionally, we are moving towards an event-sourcing, asynchronous architecture to build further fault tolerance. Implementing robust monitoring and alerting systems helps detect issues early and respond quickly.
Reactively, having a well-defined incident response plan and operational procedures is essential. This plan should include steps for quick recovery and minimal downtime and be regularly tested and updated to adapt to new challenges and technologies.
Impact of Future Technological Advancement on enterprise Operations
In the next 3-5 years, technological advancements such as artificial intelligence (AI), machine learning (ML) and cloud computing are expected to have the greatest impact on enterprise operations. AI and ML can enhance decision-making processes, automate routine tasks and provide deeper insights into data. These benefits span across building differentiations for our business stakeholders, optimizing our operations and assisting our engineering team in application development. In 2024, we began piloting Gen AI to assist our engineers in developing software and have found significant efficiency gains.
Cloud computing offers scalability, flexibility and costefficiency, enabling organizations to adapt quickly to changing demands. We have been on this journey for a few years and I believe that Gen AI will accelerate our cloud migration.
To stay ahead of the curve, organizations should invest in these technologies now, build a culture of continuous learning and foster collaboration across departments to integrate these advancements effectively. Every year, my organization establishes learning and certification goals so that our teams can continue to improve.
Advice for Aspiring Leaders in Enterprise Technology and Security
For aspiring leaders in enterprise technology and security, especially those aiming to work within the public sector, it is essential to focus on building a robust foundation in both technical and leadership skills.
As we advance in our careers and begin to lead large teams or "teams of teams," it is crucial to align our organization with core principles. At Anywhere Real Estate, our t e c h n o l o g y team anchors its core principles on quality, craftsmanship, deployment and delivering business value.
As technology leaders, staying abreast of the latest technological trends and advancements is vital. However, with new technology emerging daily, it is imperative to focus on how our technology offerings differentiate our business. At Anywhere Real Estate, I consistently challenge my leadership team to evaluate whether the software we develop adds value for our agents, franchises, buyers, sellers and employees.
Although technology spans across industries, I continue to find unique challenges and regulatory requirements in every sector I have worked in, including healthcare, payment and real estate. Therefore, understanding your industry and maintaining regular communication with your business partners is crucial to our success as technology executives. Ultimately, our job is to improve business outcomes.
Finally, I believe that the key to success lies in building a technology team that is passionate about creating world-class software. We dedicate significant energy to assembling the right team, one that shares our commitment to excellence and innovation.
London : The 3rd edition of the London Climate Technology Show concluded last week, paving a vital roadmap towards fully decarbonising our planet through sustainable technologies. The event brought together policymakers, eco-technology leaders, industry professionals, and innovators, all unified in their call for an immediate shift to sustainable and green solutions to secure a better future for the planet.
The two-day event opened on 27th November with an inspiring keynote by Felicity Burch, Executive Director of the Responsible Technology Adoption Unit at the Department for Science, Innovation, and Technology (DSIT), who spoke about AI Innovation in Clean Energy and the DSIT's Manchester Prize . Following her, Ing. Abigail Cutajar, CEO of the Climate Action Authority, talked about Pioneering the Surge Towards Climate and Energy Transitions.
The conference unfolded over two dynamic days, featuring a packed agenda of insightful presentations and engaging panel discussions. It delved into actionable strategies for decarbonisation, advancements in AgriTech, the evolving carbon market, eco-funds, energy, CCS, built environment and other groundbreaking innovations in climate technology.
Notable discussions highlighted the need for farmers to balance carbon stewardship with food production over the next few decades, the importance of consistent government policies to enable businesses to plan and innovate effectively, and the urgency of addressing digital and engineering skill shortages to ensure a successful green energy transition. Industry experts also called for common sustainability metrics to measure corporate efforts fairly, emphasized the value of collaboration over competition to accelerate the green transition, and underscored the need for farmers to access landscape-level data to enhance biodiversity.
The exhibition hall featured groundbreaking innovations and solutions in sustainability and climate technology, including carbon capture and storage (CCS) from companies like CGI and Terra CO2 Technology, carbon management and accounting solutions by Greenly and Gaia Carbon Accounting, and emerging climate technologies from innovators such as Nabla Flow and Luna 9. Other exhibitors showcased AI-driven solutions, sustainable energy systems, and innovative carbon reduction technologies, presenting a comprehensive snapshot of the future of climate tech.
#CTS24 also hosted interactive side events, including startup acceleration programs and hands-on workshops, providing participants with opportunities for learning, networking, and collaboration. These sessions empowered attendees to adopt transformative technologies and take decisive climate action.
Attendee Experiences
The event received overwhelming positive feedback:
● Mark Haley , Co-founder of Cero3, shared, "We’re so proud to have unveiled our sustainable travel planner. The feedback and interest exceeded our expectations."
● Satyajit Mohanan , Projects and Business Development Coordinator at Cambridge Cleantech, remarked, "It was a pleasure to be part of this event. I met amazing people and look forward to the next edition."
● Dennis Chacko , Senior Sales Manager at the British Board of Agreement, shared his excitement over a unique sustainable pen: "Once used, you can plant it to grow something new—a powerful reminder of how everyday items can contribute to a greener future."
As this successful edition concludes, the organisers are already planning for a bigger, more impactful 4th Edition , with expanded content and greater opportunities to drive meaningful change toward a sustainable future.
...Read more
The increasing human population and demand for clothing are inevitable, but manufacturers must balance their efforts without overextending themselves. AI can help meet demand without exceeding supply, ensuring the sustainability of the planet's finite resources.
Apparel manufacturing uses AI in the following ways:
Enhancing the grading of materials: Although the human eye is a remarkable instrument, it is also fallible. Grading yarn and other base materials are one area where AI improves quality control (QC).
As a result of applying AI to this area, cost savings are realized, and the fundamental materials used in apparel manufacturing can be graded more precisely. Thus, AI can maintain a higher standard for materials than humans alone, thereby increasing the quality of finished garments.
Increasing the accuracy of final product inspections: A piece of fruit can even be discerned from its skin if it has been bruised through machine learning and computer vision.
Textiles and apparel manufacturing are equally inspiring applications. The condition and salability of newly made and previously worn garments can be assessed by algorithms coupled with specialty illumination systems. By measuring the amount of light that is transmitted and reflected, AI can determine whether a piece of fabric or a garment meets current quality standards at a glance.
The likelihood of Type I and Type II errors in a manufacturing setting was 17.8 percent and 29.8 percent, respectively. In the former case, inspectors miss real defects, while in the latter, false positives are made.
Apparel manufacturers can keep costs and errors down by using AI-powered automated inspection software. Identifying substandard yarn early in the manufacturing process can deliver value throughout the supply chain.
A tailor-made solution for the apparel industry: Artificial intelligence
Another area where AI can shine is sustainable and customized manufacturing. To facilitate cheaper and less resource-intensive custom clothing manufacturing, modern imaging techniques allow end-users to create 3D renderings of their bodies. ...Read more
Practical technology is catalyzing sector convergence, which entails the dissolution of conventional distinctions among diverse industries. This phenomenon fosters novel business paradigms, value constellations, and prospects, enabling organizations to harness technologies and proficiencies beyond their primary domain.
Key Technological Catalysts
Several transformative technologies are serving as the primary drivers of industry convergence, providing the infrastructure and capabilities that enable cross-sector collaboration and the creation of new value. The Internet of Things (IoT) connects physical assets to digital networks, generating vast streams of data that integrate physical and virtual operations. For example, smartwatches and fitness trackers, initially consumer electronics, now serve the healthcare sector by supporting remote patient monitoring and preventative care. Artificial Intelligence (AI) and Machine Learning (ML) build on this data by enabling advanced analytics, driving smarter decision-making, and delivering hyper-personalized services across various industries. Retailers utilize AI to predict consumer trends, optimize supply chains, and personalize shopping experiences. At the same time, financial institutions leverage it for fraud detection and algorithmic trading, thereby blurring the boundaries between technology and traditional banking. Blockchain adds another dimension by offering a secure, transparent framework for managing transactions and data across multiple parties, streamlining cross-sector collaboration in areas such as supply chain management by reducing reliance on intermediaries. The rollout of 5G connectivity provides the speed and low latency necessary to support these technologies at scale, enabling real-time communication between devices and seamless integration across various industries. Autonomous vehicles, for instance, depend on instantaneous connectivity with smart city infrastructure and other cars, exemplifying the convergence of automotive, telecommunications, and urban planning.
Impact on Business and Society
Sector convergence is profoundly altering conventional business paradigms. A single product or service no longer defines enterprises; instead, they are evolving into comprehensive ecosystems that deliver an array of integrated solutions. This evolution fosters novel opportunities for innovation, concurrently introducing complexities such as navigating intricate regulatory frameworks and managing data privacy across disparate sectors. From a consumer perspective, this convergence facilitates enhanced convenience, personalization, and seamless experiences; however, it also raises concerns regarding data security and market dominance. As the trajectory of applied technology continues its advancement, the demarcations between industries will inevitably diminish, thereby ushering in a future characterized by interconnected and integrated services.
Ultimately, applied technology transcends mere efficiency; it represents a fundamental force for change, reshaping the very structure of our economy. The future will be defined by ecosystems of integrated services, where companies succeed not by dominating a single sector, but by seamlessly connecting their offerings with others. This era of convergence promises unprecedented innovation and convenience for consumers. Yet, it also necessitates a proactive approach from businesses and policymakers to navigate the challenges of regulation, data privacy, and market power. Embracing this paradigm shift is crucial for companies seeking to develop in a world where the distinctions between sectors no longer exist. ...Read more
SCADA systems have long formed the backbone of industrial automation. They play a central role in many processes, from manufacturing to utility management, providing an overview and regulation. With the advancement of technology, the future looks set to change considerably for SCADA systems. Emerging trends redefine how SCADA works, further enhancing its capabilities and integrating it into the bigger context of industrial technology.
As it has evolved, SCADA has become integrated with the Internet of Things (IoT), generating massive data that leads to better decisions and process optimization. SCADA systems have begun integrating with IoT devices to provide more accurate and timely data across numerous inputs, improving operational efficiency and giving more profound insights into system performance.
It is revolutionizing the industry by adopting scalable, flexible, and cost-effective solutions that are much sought after by industrial requirements. These enable remote access to system data and controls, making management and troubleshooting easier. The shift towards the cloud has improved data storage and analysis capabilities for robust analytics and historical data review.
Cybersecurity is essential because SCADA systems are rapidly intertwining with other digital platforms. With increased cyber threats today, more security systems are needed to protect sensitive industrial information and ensure the system's integrity. Future SCADA systems will likely incorporate more complex cybersecurity features, including advanced encryptions, multi-factor authentication, and continuous monitoring against potential threats. Advanced security protocols would be crucial in protecting these systems from cyberattacks while ensuring the dependability of critical infrastructure.
AI and machine learning are also increasingly making headlines in the future of SCADA systems. AI algorithms can read vast volumes of data generated by SCADA systems to identify trends, predict when a piece of equipment needs to be serviced, and optimize all related processes. AI-powered predictive analytics can help prevent equipment failures, minimize time loss, and enhance system efficiency. Thus, AI in SCADA has marked a significant milestone in managing industrial processes more proactively, intelligently, and streamlined.
The trend toward edge computing impacts SCADA systems. Edge computing is a form of data processing closer to the source rather than being sent to the centralized cloud or data center. Since this reduces latency and improves response times, it also reduces the amount of data needing to be transmitted over networks. This can enhance SCADA's real-time monitoring and control, making management decisions more efficient. ...Read more