Business Technology Roundtable

Every enterprise racing to deploy Agentic AI is making an infrastructure decision it may not recognize as one. When an AI agent connects to internal systems and proprietary content, the protocol governing that connection determines whether the enterprise controls the terms of access or cedes them by default. Model Context Protocol (MCP) has become the standard linking agents to backend data and tools, and it is spreading through corporate technology stacks faster than the governance frameworks meant to secure it.  For CIOs and CISOs, this stopped being a developer tooling question months ago. It is now a sovereignty question: who defines the boundary between an AI agent and a company's proprietary intelligence. The MCP Adoption Security Gap Gartner projects that by 2028, 25 percent of all enterprise Generative AI (GenAI) applications will experience at least five minor security incidents per year, up from 9 percent in 2025. That trajectory tracks closely with how fast MCP has been ...

The public internet, long treated as an inexhaustible resource for training large language models, has run dry. Not in terms of raw volume, but in terms of the cognitive density that frontier AI now requires. Research I published through GeoActive Group's Applied-AI Initiative confirms what a growing number of senior researchers have quietly acknowledged: the next phase of the AI race is being won or lost on access to human tacit knowledge, and the leading tech vendors have already restructured their organizations to capture it. This is not an incremental refinement to existing AI training methodology. It is a wholesale reorientation of how the most resource-intensive companies in the world are deploying their most valuable internal asset: the unwritten reasoning of their best people. The Structural Bottleneck Driving This Shift Three converging constraints have forced this strategic pivot. First, models trained on generic web content have hit a reasoning ceiling. They perform ade...

Economic growth is fueled by strategic investment. Venture capital (VC) has quietly become one of the most consequential forces in the global networked economy, yet most C-suite leaders engage with it only at the margins. That needs to change. A landmark new report from the World Economic Forum and Stanford Graduate School of Business, released this month, offers a comprehensive and at times sobering assessment of where the VC industry stands and where it is headed. For senior executives navigating technology strategy, capital allocation, and competitive positioning, the findings carry direct implications. The Scale of the Opportunity and the Strain Beneath It VC assets under management have grown more than sixfold since 2008, reaching $3.4 trillion globally in 2025. Seven of the ten largest companies in the world by market capitalization, including Apple, NVIDIA, and Amazon, received venture backing in their early stages. Among U.S. public companies founded in the past 50 years, VC-ba...

The global transition toward artificial intelligence (AI) has reached a critical juncture, marking a fundamental move from theoretical exploration to the large-scale implementation of Applied AI Initiatives . Applied artificial intelligence refers specifically to the practical deployment of AI technologies and methodologies to resolve discrete real-world challenges and generate measurable organizational value.  Unlike theoretical AI research, which prioritizes the advancement of fundamental science and the exploration of hypothetical machine intelligence, Applied-AI is strictly purpose-driven and practical implementation-oriented. Success in this domain is no longer measured by academic citations or AI lab breakthroughs, but by business impact, operational efficiency, and tangible societal outcomes. Between 2023 and 2025, Applied-AI consistently maintained the highest innovation scores among emerging technologies and ranked in the top five for global investment activity. As the ind...

This report is the first in a series of research-based editorials that profile the leading artificial intelligence "AI Stack" advantages, from the large enterprise senior executive perspective. Your Strategic Advantage in The AI Era The enterprise AI market is not just growing; it's exploding, with projections reaching hundreds of billions of dollars by 2030. For large enterprises, the strategic implementation of Applied-AI is no longer optional — it is the new frontier for long-term competitive advantage. The core challenge has shifted from AI experimentation to deploying scalable solutions that deliver tangible business outcomes, such as significant cost savings, new revenue streams, and superior customer experiences. However, hurdles like data silos, talent shortages, and proving value are significant. This advisory guidance makes the case for a strategic Applied-AI Initiative built on the Google AI stack. Google Cloud has established itself as a "Full-Stack Inno...

The telecommunications sector is at a pivotal intersection of technological evolution and digital transformation. What was once primarily focused on connectivity infrastructure has now emerged as a critical enabler and adopter of artificial intelligence (AI). As telcos serve billions of customers worldwide, their embrace of AI represents not merely an operational upgrade but a fundamental reimagining of how communication networks are built, managed, and monetized. From Pilots to Production: AI Goes Mainstream The most striking revelation from NVIDIA's "2025 State of AI in Telecommunications" survey is the velocity of adoption. Nearly all telecom companies are now actively engaged with AI, either deploying it in production or rigorously assessing its potential to create value. This represents a significant leap from just two years ago. More importantly, the industry has crossed the chasm from experimentation to implementation, with 49 percent of respondents actively using ...

While many industries grapple with artificial intelligence (AI) adoption, healthcare and life sciences have emerged as unexpected frontrunners in the Applied-AI transformation. This isn't merely about early adoption; it's about meaningful deployment at scale. The healthcare sector has decisively moved beyond the experimental phase, transforming AI from a technological curiosity into an operational necessity, reshaping everything from drug discovery to clinical documentation. What makes this transformation particularly compelling is its breadth. Unlike other sectors where AI applications remain narrowly focused, healthcare organizations are deploying AI across an extraordinarily diverse range of use cases — from analyzing medical imagery to accelerating pharmaceutical research, from optimizing hospital workflows to personalizing treatment protocols. This multi-dimensional adoption reflects both the complexity of healthcare challenges and the sector's willingness to embrace i...

The OECD’s latest report, "Governing with Artificial Intelligence: The State of Play and Way Forward in Core Government Functions", is an indispensable blueprint for public sector digital transformation. The analysis confirms what many leaders already suspect: Artificial Intelligence (AI) is no longer an optional add-on but the definitive next frontier in the digital government journey, offering the potential to fundamentally reshape how the state operates, delivers value, and maintains fiscal integrity. The imperative for modern governance is clear: deliver more value to citizens with greater efficiency and impeccable integrity. Applied-AI offers the transformative power to move beyond incremental improvements and achieve systemic, high-impact public sector transformation. The Productivity and Prudence Dividend The most compelling case for embracing AI in government centers on its potential to unlock unprecedented employee productivity and cost efficiency levels. Public ser...

Business technology investment continues to evolve. During the last decade, I've had a front-row seat to the meteoric global rise of Artificial Intelligence (AI) and its transformative impact across industries. The AI Consulting professional services market has emerged as a critical enabler of this transformation revolution, helping organizations navigate the complexities of AI adoption and implementation. The global AI consulting market is experiencing ongoing growth, with forecasts indicating it will reach $72.5 billion by 2025. This remarkable expansion is fueled by a compound annual growth rate (CAGR) of 40.3 percent from 2020 to 2027, highlighting the insatiable appetite for broad AI expertise and proven experience. The AI Consulting Market Analysis One of the most striking statistics is that over 80 percent of AI consulting firms report increased demand for their professional services in the past year. This surge in demand is not limited to a single sector but spans across va...