Justin Greis

06/16/2026

Most organizations already have access to powerful AI capabilities. The challenge is turning those capabilities into measurable business outcomes by connecting data, workflows, governance, security, and operating models.

As I shared with CIO Online, "Enterprise AI is moving from a technology conversation to an ex*****on conversation, and time-to-value is becoming the new battleground for competitive advantage."

I appreciated the opportunity to contribute to this discussion on Salesforce's acquisition of Fin and what it signals about where enterprise AI adoption is heading.

Thanks to Evan Schuman and CIO Online for including my perspective.

📊 For the past several years, the conversation has focused on models, capabilities, and technical breakthroughs. Increasingly, the real challenge is ex*****on.

Organizations already have access to powerful AI technologies. The harder problem is connecting data, workflows, governance, security, and business processes in a way that delivers measurable business outcomes.

As our CEO Justin Greis recently shared with CIO:

“Enterprise AI is moving from a technology conversation to an ex*****on conversation, and time-to-value is becoming the new battleground for competitive advantage.”

That shift helps explain why we're seeing accelerated investment, acquisitions, and consolidation across the AI ecosystem. The winners won't simply be the companies with the most advanced technology. They'll be the ones that help enterprises realize value faster and with less complexity.

We're pleased to contribute to CIO's analysis of Salesforce's acquisition of Fin and what it signals about the future of enterprise AI adoption.

🔗 Link to article: https://hubs.la/Q04lxp7m0

06/14/2026

🚀 The world of consulting and professional services at large is changing like never before. For those with deep expertise and the humanity to make it stick, there has never been a better, more exciting time to be in these converging professions!

I shared my thoughts on the role of Forward Deployed Engineers, Consultants, contractors, and professional services - in the age of AI - in Evan Schuman's latest Computerworld article.

IT leaders are increasingly turning to forward-deployed engineers from AI vendors for help with AI deployments. Here’s what you need to know before taking the FDE plunge.

06/10/2026

📌 A very cool milestone on our journey to build something special!

🙏 Huge thanks to Scott Slavick at Barack Ferrazzano Kirschbaum & Nagelberg LLP for his guidance and support along the way.

06/03/2026

AI is changing cybersecurity in an important way.

For years, the challenge was visibility - finding vulnerabilities before attackers did.

Now AI is making vulnerabilities easier to find. The real challenge is becoming remediation.

As discovery accelerates, the bottleneck shifts to prioritizing, patching, and fixing issues at scale.

I enjoyed discussing this shift with Evan Schuman for his recent article on Anthropic’s Project Glasswing.

See the acceligence post below for more.

🔎 Cybersecurity has long been treated as a vulnerability discovery problem, but AI is proving it was a remediation problem all along.

Projects like Anthropic's Glasswing are accelerating vulnerability discovery at a scale we've never seen before. That's good news for defenders - but it also exposes a hard truth: most organizations already struggle to validate, prioritize, patch, test, and deploy fixes fast enough.

If AI can identify vulnerabilities 10x or 100x faster than humans, the bottleneck doesn't disappear. It simply moves downstream. Organizations may soon find themselves with unprecedented visibility into risk while simultaneously becoming overwhelmed by the sheer volume of issues requiring action.

The next challenge in cybersecurity won't be finding vulnerabilities. It will be deciding which ones to fix first.

Thank you to Evan Schuman for the thoughtful discussion and for capturing this important shift in such an insightful article, "Anthropic grants Project Glasswing access to 150 more companies, with a focus on critical infrastructure."

👇 Link to CSO and CIO article in the comments below

06/03/2026

Appreciate Evan Schuman featuring my perspective in this discussion on one of the biggest challenges facing enterprise AI adoption: pricing.

As organizations move from experimentation to enterprise-scale deployment, the conversation is shifting beyond model performance and toward a more fundamental question: how should AI be valued?

My view is that much of the market is still trying to fit AI into traditional infrastructure pricing models, when AI is increasingly being used to augment work, transform processes, and create business outcomes.

The opportunity ahead isn’t simply finding better pricing mechanisms. It’s creating stronger alignment between technology investments, business objectives, and measurable value.

As AI capabilities continue to mature, I expect pricing models, governance approaches, and value realization frameworks to evolve alongside them.

And in the meantime, token prices are climbing higher and higher! To be expected as adoption grows…

Worth a read for leaders thinking through the next phase of AI adoption.

📈 AI pricing remains one of the most important conversations facing enterprise leaders today.

As AI evolves from a technology tool into a business capability, organizations are rethinking how they evaluate value, investment, and outcomes.

Three key takeaways from this discussion:

🏆 AI success should be measured by business impact, not technical consumption metrics alone.

💰 Pricing models will continue to evolve as organizations gain greater clarity on how AI creates value across the enterprise.

🔭 Strong governance, clear objectives, and executive accountability remain the foundation of successful AI adoption.

Appreciate Evan Schuman for including our perspective in this timely conversation about the future of enterprise AI. Check out his latest ComputerWorld article titled, "The AI pricing conundrum - it started as a nightmare, now it’s worse."

👇 Link to the full article in the comments below.

06/03/2026

📈 AI pricing remains one of the most important conversations facing enterprise leaders today.

As AI evolves from a technology tool into a business capability, organizations are rethinking how they evaluate value, investment, and outcomes.

Three key takeaways from this discussion:

🏆 AI success should be measured by business impact, not technical consumption metrics alone.

💰 Pricing models will continue to evolve as organizations gain greater clarity on how AI creates value across the enterprise.

🔭 Strong governance, clear objectives, and executive accountability remain the foundation of successful AI adoption.

Appreciate Evan Schuman for including our perspective in this timely conversation about the future of enterprise AI. Check out his latest ComputerWorld article titled, "The AI pricing conundrum - it started as a nightmare, now it’s worse."

👇 Link to the full article in the comments below.

05/13/2026

🧬 A great read and set of insights by Paul Bierbusse on the power of curiosity and how to weave it into the DNA of your organization.

🔍 Most organizations say they value curiosity. Far fewer are actually designed to support it.

In his latest article, acceligence Executive Advisor Paul Bierbusse explores how culture, structure, training, and incentives either cultivate intellectual curiosity or slowly eliminate it over time. Paul's piece goes beyond leadership theory and gets into the operational realities that shape how organizations learn, adapt, and innovate.

One of the strongest themes: organizations don’t become more adaptive by accident. They become more adaptive by design, a deliberate choice that permeates leadership decisions, culture, and behavior.

A thoughtful read for leaders navigating transformation, change, and disruption.

🔗 Link to the article in the comments below

05/12/2026

The other day, my colleague Yuri Goryunov and I were out to dinner when a friend asked, “So, tell me what you guys do.”

Yuri answered instinctively: “We do what we love, with people we like, and none of the stuff we hate.”

I thought that was brilliant, and I’m officially adopting it as a mantra.

That spirit is exactly why I’m proud to share this article featuring Michael Yadgar, a friend, mentor, and acceligence Executive Advisor.

Michael’s reflections are about leadership, consulting, AI, culture, resilience, and the work that endures. But at the center of it all is a simple truth: great organizations are built by people who care deeply about the people around them.

As AI changes the mechanics of work, Michael reminds us that the human work of leadership becomes more important, not less.

Thank you, Michael, for sharing your wisdom, perspective, and humanity with all of us.

Here’s to you, my friend. 👏 👏 👏

📰 acceligence news: What endures: Michael Yadgar on five leadership principles for the AI era

acceligence Executive Advisor Michael Yadgar reflects on the leadership lessons that shaped a 32-year consulting career and why they matter even more as AI reshapes the enterprise

👉 Link to the full article in the comments.

05/06/2026

⚠️ Cyber threats target people and exploit human emotion, not just system vulnerabilities.

📱 I received an SMS phishing attempt today (one of hundreds per week) impersonating the Illinois Secretary of State and using urgency, fear, and legal language to drive action. This is exactly how modern social engineering works - exploit trust, create pressure, and trigger a reaction before verification.

A few Wednesday-worthy reminders:

👆 Never click links in unexpected text messages
✔️ Verify requests through official channels
🚩 Treat urgency as a red flag, not a call to action
📨 These sorts of attacks extend far beyond email

Cybersecurity is no longer just a tech issue. It’s a leadership, operational, and human-risk issue.

05/05/2026

🏎️ AI adoption is moving fast...and that’s a good thing!

The question I keep coming back to is simple: can we scale this without breaking the economics, especially once it’s embedded in price-sensitive products?

Pilots are easy to love, but PRODUCTION is where the math gets real.

Architecture, model choice, token usage, vendor terms, and workflow design all start to matter once AI is running inside the business every day and embedded into its DNA.

I don’t think the answer is to slow down. I think the answer is to scale smarter.

acceligence Partner and CIO, Yuri Goryunov, shares an excellent perspective on why AI cost discipline will become a bigger leadership topic in 2027, and what executives can do now to get ahead of it.

Curious how others are thinking about this: are you already modeling the cost side of AI at scale?

👇 Read the full article below or at acceligence.com: https://acceligence.com/insights/2026/05/04/scaling-ai-without-breaking-the-economics/

💡 acceligence insights: Scaling AI without breaking the economics

AI adoption is entering its next phase: not less ambition, but better economics. Leaders who pair speed with cost discipline now will be positioned to scale AI confidently, protect margins, and create lasting advantage.

🔗 Read the full article here: https://hubs.la/Q04fdfff0