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Articles by Ai TechPark
The End of the App Era? How AI Agents Could Change Software
The End of the App Era may be near. Discover how AI agents could replace traditional apps and reshape the way we use software. Strip an agent of everything it can call, and what remains is a chat window. No calendar to book into. No database to query, no payment to process, no record to update anywhere. The reasoning is impressive, and it touches absolutely nothing in the world. That dependency is worth sitting with before accepting the premise. Agents don’t replace software so much as depend on it.
Why OpenAI’s Model Pricing Could Disrupt the Economics of the AI Industry
OpenAI model pricing is reshaping AI economics, challenging providers to prove value beyond capability as inference costs fall and competition intensifies. The artificial intelligence business has devoted billions of dollars to creating a lead in its model’s capability. However, with the decreasing expense of operating sophisticated models becomes a challenge to prove who is technologically “superior” will reap commercial benefits.
AITech Interview with Simon Hall, Industry Analyst at CCW Europe
CCW Europe’s Principal Analyst Simon discusses AI in CX, examining why AI investment continues to outpace measurable returns and how leaders can bridge the gap between initial pilots and enterprise-wide deployment. Simon, could you briefly introduce your role at CCW Europe and your work across AI, business technology and customer experience? Every business strategy eventually meets reality in the customer experience. I cover that proving ground as the Principal Analyst at CCW Europe.
The Talent War for AI Researchers and Its Effect on Innovation Speed
The AI talent shortage is changing how companies compete, with research expertise increasingly shaping innovation speed and long-term technical advantage. In this day and age, computing power and capital are not sufficient to give companies a technical edge when they invest heavily in AI technology. The trickier one is whether they have people who could take those resources and make better products.
Smart Homes Get Smarter: The Role of AI in Ambient Computing
AI-powered ambient computing is transforming smart homes into intuitive spaces that anticipate needs, automate routines, and simplify everyday living. AI in ambient computing is shifting the smart home from a collection of connected devices into an intelligent environment that can interpret context, anticipate needs, and coordinate actions.
AITech Interview with Anudeep Parhar, Chief Operating Officer – Digital, Entrust
Agentic AI demands stronger identity controls and clear accountability as enterprises prepare autonomous systems for secure production use. To begin, Anudeep, tell us a little about your role as Chief Operating Officer at Entrust and how your experience has shaped your perspective on securing the next generation of AI technologies.
AI-Powered Diagnostics and the Future of Early Disease Detection
How AI-Powered Diagnostics are transforming early disease detection, helping clinicians spot illness sooner and improve patient outcomes. An algorithm can outperform an experienced radiologist at spotting a lung nodule and still fail to help a single patient. That sounds like a contradiction, and it describes most of the gap between what this technology has proven and what the headlines claim it has proven. The regulatory picture gives you a sense of the scale.
AI in Manufacturing, From Predictive Maintenance to Autonomous Quality Control
AI in manufacturing is reshaping maintenance and quality control, turning early warnings into timely action while keeping production performance in focus. Data has been used by manufacturers to help detect equipment failure and track production defects for many years. The true potential now is to leverage that information and intervene before a machine fails or a defect permeates a production run.
The Race for AI Chips and How GPU Scarcity Is Reshaping Data Center Design
AI chips and GPU scarcity are changing data center design as enterprises rethink power, cooling, rack density, networking, and scalability. The race for AI chips is no longer confined to semiconductor performance. AI chip technology is redefining how enterprises plan power, cooling, networking, real estate, and capital investment across modern AI infrastructure.
AI Tech Interview with Mal Vivek CEO and Founder of Zeb
AI Tech Interview with Mal Vivek CEO and Founder of Zeb on AI driven enterprise transformation, organizational design, and business innovation. Welcome to AI-TechPark, Mal. We’re delighted to have you. Please begin by sharing a bit about your professional journey and what inspired you to start Zeb and rethink enterprise transformation. I’ve been in this business since I was about eight, watching my father and his colleagues live inside enterprise transformations.
On-Device AI and the Architectural Constraints of Mobile Inference
On-Device AI brings fast, private inference to mobile, but memory, power, and latency limits shape every architectural choice. Here’s how. Put two machines side by side and run the same language model on both. The first sits in a rack, draws several hundred watts without complaint, and pulls weights out of memory at two to three terabytes per second.
Artificial Intelligence Is Rewriting the Rules of Logistics and Supply Chains
AI in Logistics is reshaping supply chains with smarter forecasting, agile inventory planning, and faster decisions that help businesses manage disruption. For decades, supply chain planning was based on a fairly predictable premise—past demand patterns were good predictors of future demand, and an overstocked supply chain and redundant transportation capabilities served as a safety buffer against disruption.
How AI Security Is Evolving in the Age of Intelligent Agents
AI security is evolving as intelligent agents gain autonomy, access enterprise data, execute actions, and create new cybersecurity risks. AI security is entering a new phase as intelligent agents move from generating recommendations to executing business actions. Unlike conventional AI applications, agentic systems can access enterprise data, invoke tools, make decisions, and coordinate workflows with limited human intervention.
AITech Interview with John Cannava, Chief Information Officer, Ping Identity
Enterprise AI governance depends on clear agent identities, defined permissions and accountability as autonomous systems take on more complex tasks. John, your role at Ping Identity places you at the center of identity innovation. How has your perspective on digital identity evolved as AI agents move from assisting employees to acting independently across enterprise systems? For years, identity was primarily about answering a straightforward question: who is requesting access?
Strengthening Enterprise AI Performance Through Data Quality and Context
Boost Enterprise AI Performance by mastering data quality and institutional context the critical foundation most organizations overlook. When an AI system gives a disappointing answer, the first instinct in most organizations is to blame the model. Teams swap one for a newer version, adjust the prompt, add a fine-tuning step, and wait for the output to improve; sometimes the output improves a little. More often the same problems resurface a few weeks later wearing different clothes.
AI Governance and the Future of Trust, Transparency, and Control
AI governance is moving beyond compliance as autonomous systems reshape enterprise accountability, transparency, and the boundaries of human control. AI governance was once a relatively confined activity. Before a new system could be put into production, it would be subject to legal review, security assessments, and a risk assessment. After those boxes were ticked, it was increasingly passed on to other people. That’s a more difficult defence to put up.
The Strategic Impact of Autonomous AI on Business Leadership
Autonomous AI is reshaping business leadership by changing decisions, workflows, accountability, and how executives build competitive advantage. Enterprises are transitioning from experimentation to using autonomous AI to drive their operating models, in which software can reason, take action, coordinate workflows and escalate exceptions. The impact of autonomous AI isn’t limited to productivity, as it alters the way executives invest, organize the workforce, make decisions, and evaluate results.
AITech Interview with David Dowsett, SVP of AI and Engineering, AHEAD
Enterprise AI delivers lasting value when it becomes part of how organizations operate rather than remaining a collection of experiments. David, your work sits at the intersection of security, infrastructure, and enterprise transformation. How has your journey shaped the way you approach AI adoption in large organizations today? “My view of AI was shaped long before generative AI became fashionable.
Creating a Scalable AI Strategy Across Data, Talent, and Technology
Build a scalable AI strategy that connects data, talent, and technology. Learn how enterprises move AI from pilots to lasting, organization-wide impact. The fourth AI project is usually where the strategy comes apart. By that point the novelty has worn off, the executive sponsor is asking about compounding returns, and somebody in finance has noticed that each project cost roughly what the previous one cost.
Knowledge Graphs as a Strategic Foundation for Enterprise AI
Knowledge graphs in enterprise AI connect data, context, and relationships to strengthen GraphRAG, improve decision intelligence, and support trusted AI systems. It is at a tricky juncture for enterprise AI. Models are getting better, but transforming those models into business problems is largely dependent on the availability of the data that underlies them, with context, relationships, and a sense of truth.
How AI Is Becoming a True Lab Assistant in Scientific Research
AI in scientific research is accelerating discovery by helping laboratories analyze complex data, streamline experiments, and uncover patterns. The role of AI in science is evolving from being just helpful to being more operational in application, thus integrating into today’s laboratories of today. AI in research alters the way scientists operate, the time, opportunities, and knowledge they use, and the areas of their research activity.
AITech Interview with Rajit Joseph, Chief Product Officer, Copado
Enterprise AI is reshaping software delivery, with context and governance becoming essential for reliable, controlled automation. Rajit, your career has been centered on solving complex product and engineering challenges. What experiences have most influenced the way you approach AI, DevOps, and enterprise software today? I would say a few things have influenced me over my tenure. In no particular order: Start with a problem statement / use case.
The Real Business Impact of Artificial Intelligence in 2026
The business impact of artificial intelligence in 2026: why saved hours rarely reach the bottom line, and what the few winners did differently. Start at one desk an analyst who used to spend Thursday mornings pulling numbers into a report now has a draft in twenty minutes. She is not exaggerating, and she is not alone. Ask almost anyone using these tools daily, and you will hear some version of the same story. Now zoom out to the earnings statement, and that Thursday morning disappears.
From Reactive Defense to Predictive Open Source Security With AI
Open Source Security With AI is shifting security from reactive CVE response to continuous risk intelligence across code, dependencies, and supply chains. The security model for open-source software is still largely reactive, and Open Source has become fundamental to enterprise infrastructure. Organizations find a vulnerability, follow up with an advisory or CVE, evaluate exposure, prioritize remediation, and start to fix affected dependencies.
The Next Evolution of Software Development With Multi-Assistant AI
Multi-Assistant AI is reshaping software development as specialized AI assistants collaborate across coding, testing, debugging, and delivery. The software development operating paradigm is shifting towards one in which intelligence is spreading beyond a single coding assistant. Multi-Assistant AI allows businesses to deploy specific AI systems within the Software Development Lifecycle (SDLC).
AITech Interview with Kamesh Tumsi, Chief Product Officer, Smarsh
AITech Interview with Kamesh Tumsi, Chief Product Officer, Smarsh - AI-Tech Park
The Strategic Impact of Agentic AI on Identity Management
The Strategic Impact of Agentic AI on Identity Management
The Strategic Value of Vertical AI Agents for Business Leaders
The Strategic Value of Vertical AI Agents for Business Leaders - AI-Tech Park
The Business Value of Human-Agent Collaboration
The Business Value of Human-Agent Collaboration - AI-Tech Park
AITech Interview with Josh Dunham, CEO and co-founder, Reveel
AITech Interview with Josh Dunham, CEO and co-founder, Reveel - AI-Tech Park
Why Warehouses Became the Testing Ground for Real-World AI
Why Warehouses Became the Testing Ground for Real-World AI - AI-Tech Park
Adversarial Attacks Are Changing the Future of AI Security
Adversarial Attacks Are Changing the Future of AI Security - AI-Tech Park
What Does Retrieval-Augmented Generation Solve That Fine-Tuning Does Not?
Retrieval-augmented generation gives AI access to relevant, current knowledge while fine-tuning focuses more on behavior and task performance. Enterprise AI strategies increasingly face a fundamental choice between Retrieval-Augmented Generation (RAG) and fine-tuning. Both enhance the performance of the foundation models in different ways, but they address materially different problems.
AITech Interview with Neil Araujo, Chief Executive Officer of iManage
AITech Interview with Neil Araujo, Chief Executive Officer of iManage - AI-Tech Park
The Quiet Rise of Inference Optimization as a Discipline
The Quiet Rise of Inference Optimization as a Discipline - AI-Tech Park
The Real Difference Between Open-Source and Closed LLMs
The Real Difference Between Open-Source and Closed LLMs - AI-Tech Park
AITech Interview with Kory Daniels, Chief Security & Trust Officer, LevelBlue
AITech Interview with Kory Daniels, Chief Security & Trust Officer, LevelBlue - AI-Tech Park
How Enterprises Are Choosing Between Foundation Models in 2026
How Enterprises Are Choosing Between Foundation Models in 2026 - AI-Tech Park
The Compute Costs Behind Every AI Success Story
The Compute Costs Behind Every AI Success Story - AI-Tech Park
AITech Interview with Karen Kaukol, Chief Marketing Officer, Entrust
AITech Interview with Karen Kaukol, Chief Marketing Officer, Entrust - AI-Tech Park
How Enterprise Leaders Are Rethinking Build vs. Buy for AI
See how enterprise leaders are rethinking build vs. buy for AI, balancing cost, control, and flexibility to choose the right approach. A few years ago, the build vs. buy AI decision looked simple; buy for speed, build for control. But as artificial intelligence moves from experimental pilots to core business infrastructure, that old playbook doesn’t fit anymore.
The AI Singularity Debate and the Future of Machine Capability
The AI Singularity Debate and the Future of Machine Capability - AI-Tech Park
Cloud Data Migration in 2026: Best Practices for Avoiding Common Challenges
Cloud data migration in 2026 brings new risks and complexity. Learn the best practices enterprises use to avoid costly delays and overruns Cloud data migration in 2026 has moved well past the status of a routine IT upgrade. It now ranks among the top priorities for nearly every CIO, trailing only cybersecurity, and the reasoning is clear; enterprises today are moving far more than simple workloads.
Generative AI ROI: How to Measure Real Business Impact in 2026
Generative AI ROI: How to Measure Real Business Impact in 2026 - AI-Tech Park
Why Your Data Lakehouse Strategy Needs an AI Layer Right Now?
Why Your Data Lakehouse Strategy Needs an AI Layer Right Now? - AI-Tech Park
AITech Interview with Erez Tadmor, Global Field CTO, Tufin
Modern security teams rely on context-driven automation to bridge the gap between AI speed, network policy logic, and risk governance. Erez, given your global perspective as Field CTO at Tufin, what is the most significant shift you’ve witnessed in how security teams perceive AI’s role in their daily defense strategies? “The biggest shift is that security teams no longer see AI as just an analytics layer or a productivity tool.
Agentic AI Moving From Assistance to Autonomous Action
Understand how Agentic AI is changing enterprise decision-making and why organizations must prioritize governance over automation alone. Each important technological evolution comes with a story that is easy to accept. Cloud computing held the promise of flexibility. Automation promised efficiency. Generative AI spoke of productivity. Generative AI said productivity. The promise of agentic AI is not just being the agent but acting on the client’s behalf.
The Battle for AI Infrastructure Across Models, Data, and Computing Power
The Battle for AI Infrastructure Across Models, Data, and Computing Power - AI-Tech Park
AITech Interview with Bob Shaker, Chief Product and Technology Officer, ActiveState
Why secure-by-design, trusted containers, and proactive vulnerability management are becoming essential for modern enterprises. Bob, as Chief Product and Technology Officer at ActiveState, how has your three-decade journey across cybersecurity leadership roles shaped your current priorities around product strategy and secure software development? Over the past three decades, I’ve seen security evolve from a reactive discipline into a core pillar of product strategy.
The Post ChatGPT Era and Autonomous Intelligence
The Post ChatGPT Era and Autonomous Intelligence
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