Applied Intelligence Awards 2023: Meet the Nominees Across Categories

TechTarget and Informa Tech have joined forces to create a robust Digital Business Combine that reshapes how technology decision-makers access credible, original content. The integration binds TechTarget’s deep editorial discipline with Informa Tech’s expansive industry ecosystem, delivering an unparalleled network of more than 220 online properties across 10,000+ granular topics. This expansive footprint serves an audience of over 50 million professionals who rely on independent, objective reporting to inform strategic decisions, benchmark performance, and stay ahead of rapidly evolving technology trends. The combined platform emphasizes actionable intelligence, cross-functional insights, and a trusted voice in a crowded information landscape, positioning itself as a premier source for critical enterprise technology coverage.

The Digital Business Combine: Scale, Scope, and Editorial Integrity

The alliance between TechTarget and Informa Tech’s Digital Business Combine creates a scale and breadth of coverage that is difficult to match in today’s media environment. With more than 220 online properties, the network spans entire verticals, technologies, and use cases, enabling a comprehensive, 360-degree view of the technology landscape. The breadth of topics—exceeding 10,000 distinct areas—allows editors to drill into niche domains while preserving the ability to connect these details to broader business priorities. This structure supports readers who need both granular technical detail and strategic context, granting them the ability to map technical capabilities to tangible business outcomes.

Central to the model is an editorial approach built on rigor, transparency, and independence. Content from trusted sources is curated to deliver original reporting, insightful analysis, and practical guidance. Readers can expect content that not only describes what is happening in technology markets but also interprets what these developments mean for their organizations, investments, and competitive positioning. The combination emphasizes not only news and features but also data-driven perspectives that help professionals turn information into informed decisions aligned with their business priorities. In practice, this means a steady stream of reports, explainers, case studies, and thought leadership designed to illuminate the interplay between technology and business value.

Editorial teams collaborate across the network, leveraging cross-property expertise to produce harmonized coverage that respects each property’s unique audience while maintaining a consistent standard of quality. This collaboration extends to data-driven storytelling, where editors translate complex technical trends into accessible, decision-ready narratives. In addition to traditional articles, the platform integrates events, webinars, and other interactive formats to create a continuum of learning experiences that support ongoing professional development. The result is a cohesive ecosystem where insights flow across channels, enabling decision-makers to access the right information at the right time.

To maximize relevance and impact, the Digital Business Combine emphasizes audience understanding and persona-based content strategy. The platform analyzes readership patterns, engagement signals, and industry dynamics to tailor topics, formats, and delivery channels. This approach helps ensure that content remains aligned with real-world business needs, from IT procurement and cloud migrations to data governance and cybersecurity strategies. The combination also supports a broader ecosystem of services, including events and educational programming, designed to translate knowledge into concrete business outcomes.

A Unified Platform for AI, IoT, and Data-Driven Transformation

At the core of the combined network is a strong and growing emphasis on artificial intelligence, machine learning, data analytics, and related technologies. The editorial coverage spans deep learning, neural networks, predictive analytics, natural language processing (NLP), speech recognition, chatbots, and the broader suite of applied AI disciplines. By foregrounding these topics, the Digital Business Combine provides readers with a clear view of how AI and data-driven decision-making are reshaping operations across industries—from product development and customer experience to supply chain optimization and workforce planning.

Coverage is designed to connect technical insights with practical business implications. For readers implementing AI and data strategies, the platform offers content that helps translate model performance, data governance, and ethics into measurable business results. The network’s focus on applied intelligence means readers can access case studies, evaluation guides, and industry benchmarks that illuminate how organizations are deploying AI responsibly, scaling capabilities, and delivering ROI. This emphasis on applicability ensures content remains relevant for executives, data professionals, and IT leaders alike.

In addition to dedicated AI and ML content, the platform curates material across related domains, including data science, data management, data governance, and the evolving role of synthetic data in enterprise analytics. The interconnected approach helps readers see how advances in one domain—such as generative AI or foundation models—interact with data stewardship, compliance, and operational resilience. For professionals navigating complex technology stacks, the network offers a holistic view that ties together methodological advances with governance, risk management, and strategic planning.

Within this AI-centric framework, the platform also highlights notable developments and industry movements. Readers encounter profiles of AI initiatives that are advancing business transformation, such as AI science institutes, responsible AI programs, and corporate AI governance structures. The content suite includes insights into how large organizations are building capabilities around AI ethics, explainability, and bias mitigation, as well as practical considerations for deploying AI at scale. By combining technical depth with strategic context, the Digital Business Combine supports readers in making informed bets on technologies, partnerships, and governance models that align with corporate objectives.

Insights into Industry Movement: Thought Leadership, Awards, and Recognition

A prominent feature of the combined platform is its emphasis on recognized leadership and industry accolades. The editors curate coverage of notable award programs that spotlight innovation, responsible AI, and the practical business value of intelligent technologies. The Applied Intelligence Awards, for instance, gather standout projects and organizations that illustrate the power of AI, IoT, and data-driven solutions to drive performance, efficiency, and societal impact. The awards program emphasizes categories such as AI/IoT Applications of the Year, responsible AI initiatives, and leadership in AI adoption, among others. The recognition process is designed to highlight work that demonstrates the synergistic potential of AI and adjacent technologies while prioritizing ethical considerations and demonstrable outcomes.

The awards program places emphasis on projects that illustrate measurable business impact, scalability, and the ability to transform operations. Winners and finalists are presented as exemplars of how AI and IoT can be harnessed to achieve tangible improvements in areas such as safety, efficiency, customer experience, and decision support. The platform also highlights leaders in AI and technology leadership—individuals who drive cross-functional collaboration, establish governance frameworks, and foster inclusive, ethical AI practices. By featuring these profiles, the Digital Business Combine provides readers with concrete examples of best practices and strategic leadership in a rapidly evolving field.

In addition to the awards, the network highlights notable industry figures and initiatives that shape the AI and technology landscape. Profiles of executives, researchers, and corporate innovators illustrate the range of approaches organizations employ to advance digital transformation. The content explores the impact of leadership on technology strategy, talent development, and corporate citizenship, including commitments to ESG and sustainable innovation. Readers gain a sense of the broader ecosystem—the people, programs, and partnerships that collectively drive progress in AI, analytics, and intelligent systems.

Case Studies and Real-World Applications: From Autonomous Systems to Enterprise AI

The platform’s content portfolio emphasizes real-world deployments and practical outcomes. Case studies showcase how organizations apply AI, automation, and data analytics to tackle complex business challenges, optimize operations, and unlock new opportunities. Examples of focus areas include autonomous systems, robotics, predictive maintenance, and the deployment of AI-enhanced processes across manufacturing, logistics, and service industries. These narratives illustrate not only technical feasibility but also organizational change management, workforce implications, and the governance considerations necessary for successful implementation.

Several high-profile topics recur across coverage, reflecting ongoing trends in enterprise AI adoption. Self-driving technology and intelligent automation are featured through industry evaluations of infrastructure, safety standards, and regulatory considerations. Enterprises explore how AI is integrated into decision support systems, customer engagement platforms, and supply chain orchestration. The content also delves into the ethical and social dimensions of AI deployment, including concerns about bias, transparency, and accountability, and discusses how organizations are addressing these challenges through governance, audits, and diverse perspectives.

The platform also highlights the role of data strategies in enabling AI success. Discussions about data governance, data quality, data lineage, and synthetic data generation illuminate how enterprises prepare data as a foundational asset for modeling, analytics, and decision automation. Readers discover best practices for modeling, evaluation, and monitoring, as well as the tools and platforms that support scalable data pipelines and robust experimentation environments. The case studies further emphasize outcomes such as improved efficiency, reduced risk, enhanced customer experiences, and new revenue opportunities arising from intelligent automation.

In parallel with business case studies, the network features technology demonstrations and expert viewpoints that help practitioners plan and execute implementations. Technical deep-dives cover model training, deployment architectures, edge versus cloud considerations, and the integration of AI into existing tech stacks. These pieces are designed to help readers translate theory into practice, ensuring that AI initiatives align with organizational capabilities, budgets, and strategic priorities.

Global Perspectives: Regional Expansion and Market Relevance

The Digital Business Combine maintains a global lens, recognizing that technology adoption, regulatory environments, and market dynamics vary across regions. Coverage highlights how organizations in different geographies approach AI, IoT, and data-driven transformation, and how local considerations influence technology decisions. The platform emphasizes global case studies, cross-border deployments, and regional trends in cloud adoption, cybersecurity postures, and digital inclusion initiatives. This regional emphasis helps multinational enterprises benchmark themselves against peers operating in similar contexts and identify opportunities for standardization, localization, and scalable governance.

Regional perspectives also shed light on how different industries intersect with technology strategy. For example, manufacturing, energy, healthcare, and financial services each face unique challenges and regulatory landscapes that shape how they implement AI and analytics. The platform translates these variations into actionable guidance, enabling readers to learn from diverse implementations and tailor insights to their own sectorial context. In doing so, it fosters a global community of practitioners who can share lessons learned, best practices, and success metrics across borders.

The global view further supports the events and educational programs offered by the combined network. Attendees can benefit from sessions that cater to regional needs, including regulatory updates, local market dynamics, and region-specific use cases. The events program becomes a bridge between global trends and local execution, helping professionals connect with peers, vendors, and thought leaders who share a common interest in advancing enterprise technology in their markets.

Leadership in Responsible AI, Governance, and Ethical Practice

A strong emphasis on responsible AI and governance runs through the platform’s content strategy. The network highlights initiatives that address AI ethics, explainability, and fairness, acknowledging that responsible AI is essential to building trust and sustaining long-term enterprise value. Editors spotlight frameworks,Center for Excellence models, and industry examples that illustrate how organizations establish oversight, establish accountable decision-making, and audit AI systems for bias and safety.

Readers encounter practical guidance on evaluating algorithms for bias and fairness, retraining models, and monitoring performance in production. The coverage underscores the importance of transparency, reproducibility, and accountability in AI deployments, particularly in high-stakes domains like health care, finance, and public sector applications. By focusing on ethics and governance, the platform helps readers navigate regulatory expectations, stakeholder concerns, and the need for robust risk management alongside innovation.

The content also addresses trust in AI from a user and consumer perspective, examining how organizations communicate AI capabilities, protect privacy, and ensure data security. The discussions extend to policy considerations, governance structures, and the social implications of intelligent systems. In this way, the Digital Business Combine positions itself not only as a source of technical knowledge but also as a guide to responsible leadership in the era of AI-enabled business.

Innovative Solutions and Vendor Leadership: Notable Companies and Technologies

Within its comprehensive coverage, the platform spotlights notable companies and breakthrough technologies that exemplify leadership in the AI and enterprise tech space. Each profile illustrates how organizations translate research into market-ready solutions, and how they position themselves to address evolving customer needs. Examples include advanced AI infrastructure, specialized hardware accelerators, and software platforms designed to streamline AI development, deployment, and governance.

Key players highlighted include companies advancing in areas such as AI-powered safety, autonomous systems, data-centric AI, and scalable compute architectures. The profiles provide context on strategic priorities, milestones, and the practical impact of these innovations on enterprises seeking competitive advantages. Readers gain a panoramic view of the landscape, from semiconductor and hardware innovations to software ecosystems that enable scalable AI, ML, and data analytics across industries.

In showcasing these leaders, the platform also delves into the ecosystems around these technologies—partnerships, interoperability standards, and collaboration models that accelerate adoption. The analyses help readers understand not only what is technically possible, but how practical integration occurs in real-world environments, including considerations for procurement, implementation timelines, and change management. This holistic perspective supports readers in making informed decisions about technology investments and strategic direction.

Applications in Industry Vertical Contexts: Manufacturing, Healthcare, and Beyond

The platform’s content extends across multiple verticals, translating AI and data capabilities into sector-specific insights. In manufacturing and industrial contexts, automation, robotics, and intelligent process optimization drive efficiency, reduce downtime, and improve quality. In healthcare, AI-enabled analytics and predictive modeling support better patient outcomes, operational efficiency, and population health management, while ensuring compliance with privacy and safety standards. In finance, AI and data analytics power fraud detection, risk assessment, and customer insights. In energy, AI can optimize grid operations, demand forecasting, and predictive maintenance. Across sectors, the content highlights implementation considerations, governance implications, and workforce implications as organizations adopt these advanced technologies.

Vertical coverage also addresses the regulatory, ethical, and societal dimensions unique to each industry. Readers gain an understanding of how sector-specific requirements influence data management practices, model governance, and the allocation of resources for monitoring and updating AI systems. The platform emphasizes the importance of cross-functional collaboration—between IT, data science, compliance, legal, and operations—to ensure that AI initiatives align with organizational goals and regulatory expectations.

Business leaders and practitioners can also access sector-focused case studies that illustrate successful transformations. These narratives demonstrate how organizations design, deploy, and scale AI-powered solutions within the constraints and opportunities of their respective industries. By presenting real-world outcomes, the platform supports practitioners in selecting appropriate use cases, tailoring solutions to their operational realities, and communicating value to stakeholders.

Data, Analytics, and the Roadmap for the Digital Enterprise

Data strategy sits at the heart of enterprise AI and analytics initiatives. The platform emphasizes how data governance, data quality, data lineage, and data privacy enable successful AI deployments. Readers learn about building scalable data pipelines, selecting appropriate data platforms, and creating reliable environments for experimentation and production. The coverage also explores synthetic data as a tool for training and validating models when real-world data is limited or sensitive, discussing its benefits and limitations within responsible AI practices.

The roadmap for the digital enterprise commonly includes evaluating AI software and hardware choices, balancing on-premises, cloud, and edge computing considerations, and planning for interoperability with existing systems. The platform’s articles discuss best practices for model training, validation, deployment, monitoring, and ongoing maintenance. Readers gain guidance on choosing architectures that support resilience, latency requirements, and cost efficiency while enabling rapid iteration and experimentation.

A focus on ROI and business value anchors the data and analytics discourse. The content helps executives connect technical outcomes to business metrics, such as revenue growth, cost savings, operational efficiency, customer satisfaction, and competitive differentiation. This emphasis on measurable impact supports leadership in prioritizing initiatives, securing funding, and aligning AI and analytics programs with broader corporate strategy.

Community, Events, and Continuous Learning

The Digital Business Combine extends beyond written content to include events, webinars, podcasts, and multimedia educational experiences. These forums foster community engagement, knowledge sharing, and real-time dialogue among practitioners, researchers, and decision-makers. Attendees gain access to expert-led sessions, demonstrations of emerging technologies, and opportunities to network with peers and potential collaborators. The events program serves as a catalyst for learning, enabling organizations to stay current with trends, evaluate vendors, and accelerate internal capabilities through hands-on experiences and peer feedback.

Educational offerings are designed to support continuous professional development. By combining editorial coverage with live and on-demand learning, the platform helps professionals stay up to date in a rapidly changing environment. The breadth of formats—articles, videos, case studies, and interactive sessions—ensures diverse learning preferences are met. For organizations, participation in these events can translate into practical outcomes, such as accelerated AI pilots, better vendor selections, and stronger governance models.

The community aspect also includes engagement with industry leaders and researchers who shape the direction of AI, IoT, and data-driven transformation. Thought leadership sessions, panel discussions, and Q&A formats provide readers with access to diverse perspectives, enabling them to challenge assumptions, refine strategies, and build networks that propel innovation. The result is a vibrant ecosystem that supports ongoing learning and collaboration across regions, industries, and disciplines.

Conclusion

The alliance between TechTarget and Informa Tech’s Digital Business Combine represents more than a simple consolidation of assets; it embodies a comprehensive platform designed to empower technology leaders with credible, actionable insights across a vast spectrum of topics. By uniting a network of hundreds of properties, thousands of topics, and millions of professionals under a single, coherent editorial framework, the combined entity offers unmatched breadth and depth. The emphasis on original reporting, objective analysis, and practical guidance positions the platform as a trusted partner for strategic decision-making in an era defined by AI, automation, data governance, and digital transformation.

This integrated ecosystem prioritizes clarity, governance, and practical impact. Readers gain access to in-depth AI and ML coverage, real-world case studies, industry insights, and leadership perspectives that illuminate how technology translates into tangible business value. The platform’s commitment to responsible AI, ethical practice, and transparent governance further reinforces its role as a credible source in a landscape where trust is paramount. By combining editorial excellence with a global network of properties, events, and communities, TechTarget and Informa Tech create a powerful resource that supports organizations as they navigate complex technology choices, optimize performance, and pursue sustainable innovation.

The resulting resource is not only a catalog of information but a dynamic engine for decision support. It equips decision-makers with the contextual understanding, data-driven perspectives, and practical guidance necessary to align technology investments with strategic objectives. In a world where technology evolves at a rapid pace, the Digital Business Combine offers a stable, trustworthy foundation for enterprises seeking to stay informed, act decisively, and lead with confidence. The ongoing integration promises to deepen collaboration, expand coverage, and refine the ways professionals access and apply knowledge—ensuring that readers remain equipped to turn information into measurable business outcomes.