Opinion

If you are interested in having your voice heard on TechTarget's Opinion page, please read our editorial guidelines and fill out the submission form here.

• 

  We need responsible people to drive responsible AI

  Rules alone can't make AI safe -- IAPP's Trevor Hughes argues it's time to build and scale a professionalized AI governance workforce before risks outpace oversight.

  J. Trevor Hughes, president and CEO of IAPP • Oct. 14, 2026

• 

  Data centers aren’t enough: The real AI infrastructure is people

  The AI race isn't won by chips alone -- it's won by preparing people to use them. Vasileios Maroulas explains that without workforce readiness, technology investments fall short.

  Vasileios Maroulas, PhD, associate vice chancellor, University of Tennessee, Knoxville • Oct. 6, 2026

• 

  Evaluating agentic AI for demand forecasting

  Agentic AI offers autonomous, goal-driven demand forecasting that adapts to disruption. CIOs must assess data infrastructure, explainability, integration costs and phased rollouts.

  Kishan Kumar • Oct. 1, 2026

• 

  The hidden cost of getting AI decisions wrong

  FICO's Mike Trkay says the AI cost conversation focuses on tokens and models, but the real question isn't what a model costs to run -- it's what a wrong decision costs.

  Mike Trkay, CIO & chief customer officer at FICO • Oct. 1, 2026

• 

  Mind the gap, not the doom: An operational guide to AI pacing

  Business leaders should focus on near-term AI risks and capabilities gaps rather than existential debates to survive coming disruptions.

  Chris Canal, co-founder at EquiStamp • Sept. 29, 2026

• 

  AI apocalypse warnings: Safety concern or market strategy?

  Recent AI extinction warnings from industry leaders may be less about safety and more about business strategy.

  Shelly Kramer, CEO and principal analyst at Kramer&Co • Sept. 28, 2026

• 

  Why soft skills matter more in the age of AI

  AI success depends on human skills like adaptability, judgment and collaboration -- not just technical expertise. Organizations must rethink hiring to find talent that can evolve.

  Erin Rushman • Sept. 24, 2026

• 

  Beyond discovery: The real shadow AI challenge

  IT teams can now identify shadow AI tools, but remediation doesn't scale. Managing hundreds of niche AI tools requires faster approvals and distributed governance.

  John Frechette and Suzannah Hicks • Aug. 25, 2026

• 

  AI isn’t breaking higher education – it’s exposing the cracks

  Higher education is built on inherited architecture that’s based on outdated assumptions. The question isn’t what AI tools to buy, but whether the fix needs a patch or rebuild.

  Robert Clougherty • Aug. 18, 2026

• 

  HAL 9000 was right: AI guardrails matter more than perfect models

  2001: A Space Odyssey's HAL killed its crew because no one told it humans mattered more than the mission. Today's AI needs that lesson: guardrails over goals, boundaries over logic.

  Stephen Bigelow • Aug. 12, 2026

• 

  Distributed computing: The infrastructure shift AI demands

  The hyperscale era is ending. AI's energy and latency demands are driving infrastructure toward the edge -- closer to users, devices, and energy sources.

  Simon Ratcliffe • Aug. 12, 2026

• 

  How to manage the gap between enterprise AI use and AI regulation

  Companies are deploying AI across their organizations faster than lawmakers are building consistent rules to govern it, leaving CIOs to navigate an expanding patchwork of state requirements.

  Jon Polenberg • July 27, 2026

• 

  The AI metrics trap: Measuring speed but missing value

  Rising token counts and pull request throughput look impressive, but they miss where AI creates real value: preventing bad decisions and surfacing blockers before they cost time.

  Sireesha Pulipati • July 24, 2026

• 

  Why AI writing can’t be great

  In today's rapidly changing writing landscape -- just kidding. Most readers are savvy enough to recognize specific phrases as AI tells. Why does AI write like that, and why does it matter?

  Gabe Knuth • July 21, 2026

• 

  To make policy, policymakers should use AI

  Too often, policymakers base their organization's policies for AI usage on what they read in the news instead of first-hand experience working with the latest AI features.

  Gabe Knuth • July 15, 2026

• 

  Bans on AI layoffs: Current laws and what might come next

  An appellate court in China ruled that employers cannot cite AI as a reason for terminating employees. Is similar legislation likely to occur in the U.S.?

  Chris Tozzi • July 9, 2026

• 

  AI scaling is where most companies stall. Here’s why

  Expanding AI use requires new operating models, talent and mindsets -- not just more resources. Companies fail because they try to scale experiments instead of redesigning systems.

  Rodrigo Domingues • July 9, 2026

• 

  AI turns data center power into an enterprise challenge

  AI workloads are straining data center power and grid capacity, forcing enterprises to rethink workload, cloud and infrastructure strategies beyond traditional approaches.

  Varun Raj • July 2, 2026

• 

  Your AI advantage isn’t speed -- it’s judgment

  Corporate AI strategies prioritize speed, but when everyone accelerates equally, the advantage disappears. Real competitive edge comes from using AI to sharpen strategic thinking.

  Eric Dodson Greenberg • June 16, 2026

• 

  The legal mistake courts should avoid in Eightfold AI lawsuit

  The Eightfold AI class action suit threatens to stretch consumer reporting laws beyond their limits, treating AI software vendors as reporting agencies rather than tool builders.

  Jon Polenberg • June 1, 2026

• 

  Why AI systems need a boundary between reasoning and execution

  Tightly coupled AI systems create control gaps. A reasoning-execution boundary enables policy-bound, traceable and auditable execution at scale across enterprise workflows.

  Varun Raj • May 28, 2026

• 

  AI agents are only as smart as the data that feeds them

  Using business semantics is key to making AI agents deliver accurate insights. Aligning an organization's data with its business logic ensures trust and smarter decisions.

  Rashmi Choudhary • April 16, 2026

• 

  Beyond the chatbot: Engineering the agentic enterprise

  Agentic AI is taking over where chatbots leave off. These systems let enterprises automate workflows, driving operational change and doing real work.

  Ankita Devadiga • April 14, 2026

• 

  Time to rethink cloud architecture for enterprise AI

  Enterprise AI systems demand cloud architectures that emphasize persistent state, governance and adaptive infrastructure to ensure long-term reliability.

  Varun Raj • March 28, 2026

• 

  Why enterprise AI needs diagnostic intelligence

  Enterprise AI detects anomalies but can't always explain why they happen. Next up for these systems is a focus on diagnosis to enhance trust, compliance and safety.

  Rashmi Choudhary • March 25, 2026

Next