The ABC Challenge All Enterprises Face: New Book on AI, Blockchain, and Cybersecurity for Finance

CHICAGO, IL, UNITED STATES, February 12, 2026 /EINPresswire.com/ -- In a new book, ABC: AI, Blockchain, and Cybersecurity for Finance, to be published by Routledge this year, co-authors Anil Chintapalli, Dr. David Metcalf, and Dr. Max Hooper examine three critical technologies – AI, blockchain, and cybersecurity – and their integration into enterprise operating models.

"AI, blockchain, and cybersecurity ('ABC') are transforming the enterprise landscape across every single industry," says co-author Anil Chintapalli, Chairman of People360, Managing Partner at Human Capital Development, and Strategic Advisor to McKinsey & Company. "The potential lies in their ability to amplify human capital, transform industries, and address complex global socio-economic challenges at speed and scale."

The book offers insights for businesses navigating these evolving technologies. It outlines how organizations can leverage them by identifying opportunities and risks, designing enterprise strategy, building operating models and resilient infrastructure, addressing talent concerns (including agentic workforce), change management, governance, planning for execution and scaling, and achieving return on investment.

"We articulate a functional and pragmatic blueprint on these technologies, and how this will shape the future of business, operations, and the technology landscape," says co-author Dr. David Metcalf, General Partner and Director at Global Blockchain Ventures.

The 10 Critical AI Challenges

The authors identify 10 challenges pertaining to AI that enterprises face globally:

1. Lack of Clear Strategy or Use-Case Prioritization – Many enterprises jump into AI without defining why or where it creates value, leading to "shiny object syndrome" —pursuing AI for innovation theater, not for impact or business outcomes.

2. Data Fragmentation and Poor Data Quality – 80% of AI effort is often spent on data preparation to address data quality issues and data fragmentation challenges.

3. Legacy Infrastructure and Integration Barriers – Machine learning operations and data pipelines are often immature or underfunded, creating barriers for execution.

4. Talent Shortage and Organizational Readiness – Many projects fail due to "AI stuck in the lab"—not embedded into the business due to a lack of multi-functional and domain-related talent.

5. Low Trust and Resistance to Change – Change management and stakeholder education are crucial to overcome fear and friction.

6. Ethics, Bias, and Regulatory Risk – Enterprises need strong AI governance frameworks—explainability, fairness, and human oversight.

7. Scaling from Pilots to Production – Unclear ownership, lack of ROI tracking, model drift, and security risks undermine a project's ability to go from pilot to production.

8. Undefined ROI and Business Case Uncertainty – Without a strong value realization framework, leadership support fades.

9. Market Demand and Timeliness – Without a proven implementation methodology, practical outcomes are not aligned to theoretical promise.

10. Practical Knowledge Gap – Without upfront investment in addressing the knowledge gap (why, what, when, and how), project outcomes are compromised.

The authors outline solutions to address these challenges, supported by case studies.

"ABC will shape the future of our current technology and post-quantum future," says co-author Dr. Max Hooper, General Partner and Managing Director at Global Blockchain Ventures.

All three authors bring individual experience spanning technology, operations, and investments relevant to the AI, blockchain, and cybersecurity sectors, and have authored prior technology books. Anil, who also serves on the Forbes Business Council and the Fast Company Executive Board, authored a technology book on SAP published by John Wiley, while Dr. David Metcalf and Dr. Max Hooper have authored multiple publications on blockchain and related topics.

Anil Chintapalli
Human Capital Development
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