AI Innovation: Bridging the Gap Between Concept and Implementation

AI is transitioning from enhancement tool to foundational enterprise layer. Organizations must shift from tech-first approaches to strategic AI alignment to stay persistently relevant

Artificial Intelligence

"As AI adoption matures, the focus has shifted from experimentation to smart execution.”

Natalia Modjeska, Research Director, AI and Intelligent Automation

AI is rapidly evolving from a supplementary tool to a foundational enterprise layer, yet many organizations approach innovation reactively, driven by FOMO rather than strategic intent. Generative, and agentic AI experimentation often lacks alignment with the organization’s core value proposition and customer experience priorities.

The AI journey should begin with a clearly defined value statement that identifies specific business challenges or opportunities (that technology can address).

This statement must be mapped to use cases and the necessary AI and organizational capabilities. By prioritizing strategic alignment over ad hoc experimentation, enterprises can focus on solutions that yield more impactful, sustained business outcomes and stronger ROI.

This research is taken from Omdia's:

Artificial Intelligence Applications Intelligence Service

Further reading

Digital Workplace

“Voice communications have become "big data".”

Brent Kelly, Principal Analyst, UC&C

Voice communications have become "big data," generating massive amounts of valuable information for organizations and individuals through transcription, automated meeting summaries, real-time agent support, sentiment analysis, enhanced workflows, and voice-enabled customer interaction systems. Individuals now have access to powerful always-on mobile device voice assistants that record meetings, surface contextual information during conversations, and provide real-time translation.

Voice as data is bridging conceptual AI capabilities with practical implementation across business and personal contexts. The clear market winners will be contact center vendors, LLM makers, and AI professional services companies, positioned to capitalize on exploding growth in voice data processing and analytics capabilities.

This research is taken from the Omdia:

Unified Communications and Collaboration Intelligence Service

Further reading:

Channels

"Resilience as the new baseline for global manufacturing."

Lisa Lawson, Principal Analyst, Channels

AI is evolving from basic generative functions to autonomous agentic capabilities, fundamentally transforming business models and partner relationships.

By 2030, Omdia predicts a $267 billion global partner opportunity for AI services, with agentic AI commanding significant value through autonomous, continuous learning agents. Unlike generative AI that enhances productivity, agentic AI eliminates routine work entirely.

Major vendors are embedding AI into core strategies while building data moats for competitive advantage. Partners face critical opportunities addressing customer expertise gaps in implementation, governance, and security. Success requires specialized practices in data preparation, AI customization, and business process redesign, with pricing shifting from seat-based to outcome-based models.

This research is taken from Omdia's:

Channels Strategy Analysis and Partner Programs Analysis

Internet of Things

"IoT: Feeding AI to create real world value…in real time."

Andrew Brown, Research Leader, IoT

Artificial iIntelligence offers powerful in reasoning and prediction capabilities but is limited without a connection to the physical world. IoT provides that bridge, giving AI the sensors and actuators it needs to see, understand, and act in real time. According to Omdia’s end user enterprise IoT research, 34% of companies are using AI and Machine Leaning in their IoT deployments, with 44% citing it as a priority for the future.

IoT’s vast network of connected devices feeds AI with continuous data — temperature, motion, video, and more, turning abstract data into actionable intelligence. This fusion, known as AIoT, creates a feedback loop, with IoT delivering the data that powers AI, and AI delivering the intelligence that drives IoT.

This research is taken from Omdia's:

IoT Services and Platforms Intelligence Service and IoT Devices and Components Intelligence Service

Further reading:

IoT Platforms Market Tracker – 2025 Analysis

Together, they transform passive analytics into autonomous action, predict failures, optimizing systems, and adapting instantly to change. In essence, IoT makes AI tangible, scalable, and valuable, forming the foundation of the next generation of intelligent, connected infrastructure.

The artificial intelligence arms race is underway. As AI is harnessed by attackers for more adaptive ransomware and phishing campaigns, the stakes have never been higher for security teams. Firms will leverage unique combinations of machine learning, generative and agentic AI as complementary and foundational capabilities, rather than as add-on components. Building resilient, security-enabled enterprises will see a shift away from maintaining static defensive postures to adaptive frameworks, tools and policies.

The transition from concept to implementation across the attack surface will drive enterprises to embed security considerations into every layer of enterprise AI deployments, and cybersecurity for AI.

The goal will be to ensure that innovation and protection advance together rather than in opposition. However, realizing this transition will take expertise that many firms don’t have – partners and interoperable tools and platforms will be key.

This research is taken from Omdia's:

Cybersecurity Viewpoint Service, Security Operations Intelligence Service, Data and Identity Security Intelligence Service, Infrastructure Security Intelligence Service, Operational Technology (OT) and IoT Cybersecurity Intelligence Service

Cybersecurity

"AI's transformation is now a critical inflection point for cybersecurity vendors."

Adam Etherington, Research Lead, Cybersecurity

Further reading:

Data centers built for the AI era are becoming critical infrastructure that is needed to develop, deploy, and run the AI workloads that are changing our lives. Data center operators are responding to and driving this demand with significant capacity expansion, marking a substantial infrastructure commitment to AI workloads.

Alphabet’s Sundar Pichai commented that the data center construction of the past decade will be replicated in the next two years. Omdia predicts that data center capex is on target to hit $1 trillion by 2030.

Cloud and Data Center

"The data center industry is witnessing a major transformation that is driving AI's evolution from experimental workloads to deliver mission-critical business systems."

Vlad Galabov, Research Director, Enterprise Applications

This research is taken from Omdia's:

Data Center Capacity and Investment Intelligence Service, Data Center Compute Intelligence Service, Data Center Thermal Management Intelligence Service

Customer Engagement

" AI does not just enhance enterprise workflows, it completely revolutionzes them. "

Mila D’Antonio, Customer Engagement & Analyst

Artificial intelligence is transforming from a tactical enhancement tool into foundational enterprise technology that drives core business operations. Organizations are discovering that tech-first approaches yield limited results, necessitating a strategic shift toward comprehensive AI alignment that measurably improves operational efficiency, revenue generation, and customer satisfaction.

Success demands sophisticated enterprise orchestration that seamlessly integrates data flows, applications, and infrastructure across front-, middle-, and back-office functions, creating unified intelligent ecosystems.

Recent Omdia research indicates that more than a third (39%) of the companies that have realized significant or moderate value from AI-powered technology deployments, attribute their success to seamless integration with business systems. This evidence underscores the critical importance of bridging conceptual AI vision with practical, enterprise-wide implementation strategies.

This research is taken from Omdia's:

Customer Engagement Intelligence Service