Thoughts on AI: Developers, Security, and the Data Center Question

Apr 19

A perspective from the IBM i developer community · Research Edition

How I Write These Articles

My writing process is a little unconventional, but it works for me. Most of what you read here starts as a voice dictation during my morning commute — four days a week, anywhere from one to two hours on the road. I use the Obsidian note-taking app and simply dictate whatever is on my mind: raw, rambling, and often scattered across ideas — but always anchored to a central thought.

When I get home, I pull the notes down from the cloud and begin shaping them into something readable. I structure, focus, and refine until the piece is nearly done. From there, I use AI to help tighten the writing — improve clarity, sharpen the focus, and make it genuinely worth your time to read.

Important

AI does not write my content. It helps me transform unfiltered thinking into a focused, readable piece.

I supplement my thinking with research — looking for information that corroborates or adds context to my ideas. If something is contradictory but not factual, I leave it out. This edition includes those research references so you can dig further if a topic resonates with you.

1. AI for Developers

This is the topic closest to my heart. I cannot develop everything I have on my mind — I simply do not have enough time. My day job brings a constant stream of problems, requests, and projects. I want to be innovative and aware of what is next, all while maintaining and modernizing an RPG-based ERP that needs real growth to remain stable and useful.

The Numbers Are Already Striking

The adoption statistics alone are worth pausing on. As of 2025, the research shows how deeply AI coding tools have embedded themselves into day-to-day development work:

"84% of developers use or plan to use AI tools, and 41% of all code written in 2025 is AI-generated."index.dev — Developer Productivity Statistics with AI Tools 2026

"Enterprise spending on generative AI applications exploded from $600 million to $4.6 billion in 2024 — an 8x increase that signals we have moved well beyond experimentation."ksred.com — AI for Coding: Why Most Developers Get It Wrong

"The AI coding tools market has grown to an estimated $12.8 billion in 2026, up from $5.1 billion in 2024. Enterprise adoption reached a tipping point, with 78% of Fortune 500 companies now running some form of AI-assisted development in production."tech-insider.org — AI Coding Tools 2026

The Spectrum of AI Developer Activity

When I look at what developers are doing with AI today, I see a wide range of activity — from infrastructure builders to individual workflow improvement:

Building AI harnesses, MCP servers, and RAG pipelines for enterprise data access
Writing VS Code extensions and custom tooling to improve personal or team workflows
Using AI for code analysis, review, and automated documentation
Experimenting with AI-assisted code generation for enterprise platforms like RPG/ILE

I am AI-curious and want to try everything. At work, our environment is protected and we are still building our security model and governance policies. At home, my lab is a different story — my own servers, my own data, and a much more advanced AI setup. That is where I experiment freely.

The Future of AI-Generated Code

I want to flag something I see coming that is significant for every developer and development manager reading this. Gartner and MIT are pointing at the same horizon:

"Gartner predicts that by the end of 2026, 75% of developers will spend more time orchestrating and architecting than writing code directly. New roles are already emerging: AI Orchestrator, RAG Engineer, AI Guardian."firstlinesoftware.com — AI Software Development: 2026 to 2035

"When OpenAI introduced the SWE-bench software engineering benchmark in August 2024, the top model solved just 33% of real-world bugs. A year later, leading models consistently score above 70%. AI coding agents are improving at a pace that is difficult to overstate."MIT Technology Review — Rise of AI Coding

The critical variable will not be the AI itself — it will be the quality of the architects and engineers guiding it: their ability to prompt well, engineer thoughtfully, and test rigorously. The market is already signaling this. Job postings requiring experience with AI coding tools increased 340% between January 2025 and January 2026. Meanwhile, postings for pure implementation roles — jobs focused primarily on writing boilerplate — declined by 17%.

Takeaway

Developers who learn to work with these tools effectively will have a meaningful advantage. Those who do not will find a changing job market.

There is also a shadow side worth acknowledging:

"AI-generated code contains 2.74x more security vulnerabilities than human-written code. 45% of OWASP Top 10 security tests fail on AI-generated codebases. This makes human review and architectural oversight not just important — but essential."firstlinesoftware.com — AI Software Development: 2026 to 2035

2. Security and Governance

If anything is going to meter the pace of AI adoption within organizations, it is security and governance. This is not a reason to sound the alarm — it is a reason to focus.

The Governance Gap Is Real

The data on this is sobering, and it comes from some of the most credible sources in the field:

"IBM's 2025 Cost of a Data Breach Report found that AI adoption is greatly outpacing AI security and governance. 13% of organizations reported breaches of AI models or applications, and 97% of those lacked proper AI access controls. Organizations bypassing security in favor of do-it-now AI adoption are paying for it."IBM Newsroom — Cost of a Data Breach Report 2025

"63% of breached organizations either have no AI governance policy or are still developing one. One in five organizations reported a breach due to shadow AI. The average breach cost for organizations with high levels of shadow AI is $670,000 higher than those with low or no shadow AI."IBM — Cost of a Data Breach Report 2025

"According to Accenture's State of Cybersecurity Resilience 2025, 77% of organizations lack the basic data and AI security practices needed to protect critical tech infrastructure. The average AI-enabled data breach now costs $4.88 million."Harvard Business School Working Knowledge

"Stanford's 2025 AI Index Report found that AI-related security incidents jumped 56.4% in a single year, with 233 reported cases throughout 2024. U.S. federal agencies issued 59 AI-related regulations in 2024 — more than double the 25 issued in 2023."kiteworks.com — AI Data Privacy Risks: Stanford AI Index

The Path Forward

Security needs to receive the same level of investment and attention as development. We need people stepping up in this space — not to create fear, but to provide rigorous, contextual guidance that development teams can actually use. Two goals exist in tension but are not in conflict:

Getting AI into the hands of developers, thinkers, and creators
Maintaining rigorous control over enterprise systems and data

"Gartner predicts that by 2026, enterprises applying AI Trust, Risk, and Security Management (TRiSM) controls will consume at least 50% less inaccurate or illegitimate information. Effective governance is a competitive advantage, not just a cost of doing business."Gartner — AI TRiSM Controls

Watch This Space

Security and governance will be the metering valve controlling the speed of AI adoption inside organizations. Build it right the first time.

3. Data Centers: The Environmental and Community Cost

This is the one that keeps me thinking. The scale of data center construction happening right now in the United States is staggering. We have to ask some hard questions about where this is headed.

The Scale Is Difficult to Comprehend

"In 2024, global data centers consumed approximately 460 terawatt-hours of electricity, producing an estimated 182 million tons of CO2. The energy demand from data centers is projected to rise 7–12% by 2030. In the Mid-Atlantic 'Data Center Alley,' increased demand caused an 800% surge in energy prices during a 2024 capacity auction."ANSI Blog — Sustainable AI Data Centers: Energy & Emissions

"Research published in Nature Sustainability estimates that AI server deployments across the U.S. could generate an annual water footprint of 731 to 1,125 million cubic meters and additional annual carbon emissions of 24 to 44 million tons of CO2-equivalent between 2024 and 2030."Nature Sustainability — Environmental Impact of AI Servers in the USA

"Published research suggests AI systems may have a carbon footprint equivalent to that of New York City in 2025, while their water footprint could approach the global annual consumption of bottled water. Further disclosures from data center operators are urgently required."PMC / ScienceDirect — Carbon and Water Footprints of Data Centers

The Community and Transparency Problem

Beyond the headline environmental numbers is something closer to the ground that resonates with me personally — the question of what happens to the communities where these facilities land:

"Data centers are frequently entering communities under non-disclosure agreements. Builders often hide information about water usage, energy usage, air quality impacts, and emissions. Communities often do not know what they are getting into until it is too late."Lincoln Institute of Land Policy — Data Drain

"Residential electricity prices jumped 7.1% in 2025, more than double the inflation rate, and topped 20% in some states. An analysis by the Union of Concerned Scientists found that homeowners and businesses in seven states faced $4.3 billion in additional costs in 2024 from transmission projects needed to power data centers."NPR — Data Centers: Big Energy and Environmental Risks

"Between March and June 2025, community opposition led to $98 billion in data center projects being blocked or delayed. In Indianapolis, intense resident opposition caused Google to withdraw its $1 billion data center rezoning proposal. More than 230 environmental organizations have collectively called on Congress to place a national moratorium on new data centers until adequate protections are in place."Consumer Reports — AI Data Centers: Big Tech's Impact on Electric Bills, Water, and More

East Palestine and the Parallel That Keeps Me Up at Night

I live about 45 miles from East Palestine, Ohio. The parallels between what happened there and what I see happening with data center siting are not accidental — they are structural. When a small community sits in the path of a large economic or industrial force, the outcome often follows the same pattern: promises made, attention eventually fades, and the people who live there are left with less than they had.

"On February 3, 2023, a Norfolk Southern freight train carrying hazardous materials including vinyl chloride derailed in East Palestine, Ohio. An estimated 43,000 fish and animals died. Cleanup crews removed over 176,000 tons of contaminated soil. A June 2024 analysis found extreme concentrations of pollutants across a 1.4 million square kilometer area covering portions of 16 U.S. states."Wikipedia — East Palestine, Ohio, Train Derailment

"Residents of East Palestine reported long-term health problems including rashes, coughs, and sickness following the derailment. Some residents have criticized the government for downplaying health and safety concerns. Health researchers have noted that carcinogen exposures take time to result in detectable cancers, requiring long-term guaranteed medical monitoring."WSWS — East Palestine Residents Report Long-Term Health Problems

"The DOJ and EPA announced a $310 million settlement with Norfolk Southern, with the company expected to spend over $1 billion in total to address contamination and improve rail safety. While the financial settlement has been reached, residents continue to press for long-term health tracking and transparency."U.S. Department of Justice — Settlement with Norfolk Southern

I see a parallel risk with data centers. Layers of legal structures, investment vehicles, and enormous sums of money have a way of quieting the concerns of ordinary people. Billions of dollars silence voices. We know this.

Observation

Data centers may be the next military-industrial complex. The scale, economics, and political dynamics are beginning to rhyme with patterns we have seen before.

Closing Thoughts

I love using AI. I love watching what it does and the genuine good it enables. And I think it raises some of the most profound questions of our time — around security, around labor, around governance, around power, and around what happens when AI starts running on quantum computing infrastructure. Something that is simultaneously this beneficial and potentially this consequential rarely comes in the same package.

Anyone claiming to have all the answers right now probably does not understand the question. There are genuine experts — people who have been working with AI for many years. I respect them. But for most of the voices positioning themselves as the definitive voice on AI right now, we all have a long way to go.

Let us tackle security. Let us tackle the data center question. Let us make sure the people who live and work at the intersection of these decisions have a voice in how this unfolds.

Be safe. Be smart. Stay vigilant.

Executive Summary

Three critical forces are shaping the AI landscape right now:

AI for Developers — AI has moved from experimentation to production. 84% of developers now use AI tools; 41% of all code is AI-generated; the market has grown to $12.8 billion. Gartner projects developers will spend more time orchestrating than coding by end of 2026. The winning variable will be the quality of human architects and engineers guiding the process.
Security and Governance — Organizational AI adoption is outpacing security maturity at a dangerous rate. IBM's 2025 report found 97% of AI-breach victims lacked access controls; shadow AI costs organizations $670,000 more per breach. Governance is not a blocker — it is a prerequisite. Development and security teams must engage at a deeper level.
Data Centers and Community Impact — The AI infrastructure buildout is creating significant environmental, economic, and social disruption. Annual carbon footprints are estimated to rival New York City's. Community opposition has already blocked $98 billion in projects. Transparency, accountability, and community engagement are urgently needed.

Bottom line: AI's potential is extraordinary and the concerns it raises are real. Both deserve serious, honest attention.