What if the biggest cybersecurity threat facing your company is about to move faster than your team can respond?

In this episode of Between Fires and Futures, Tonya sits down with Craig Taylor, co-founder of CyberHoot, to unpack a rapidly changing cybersecurity landscape where AI can discover software vulnerabilities at machine speed, dramatically shrinking the amount of time businesses have to protect themselves. With nearly three decades of cybersecurity experience and a background in psychology, Craig explains what this shift means for IT leaders, MSPs, and mid-market organizations trying to prepare without creating panic or burning out their teams.

Craig breaks down five practical steps organizations can take now to reduce their exposure, including shrinking their internet-facing attack surface, accelerating patching, isolating or modernizing legacy systems, reducing unnecessary data storage, and improving early breach detection. He explains why traditional patching timelines may no longer be fast enough, how years of forgotten data can turn a security incident into a costly nightmare, and why leaders need to understand exactly which doors and windows into their environment have been left open.

They also explore the human side of cybersecurity and why fear-based phishing tests may actually work against the behavior companies are trying to create. Craig shares how positive reinforcement, psychological safety, and hands-on learning can help employees build lasting cybersecurity habits. As AI changes both offensive and defensive capabilities, he explains why organizations need to strengthen their technology defenses while creating a culture where employees feel confident recognizing risks, reporting mistakes, and becoming an active part of the security strategy.

Tune in to hear:

• Why AI-powered cybersecurity threats are moving from human speed to machine speed
• What the “months, not years” warning means for IT and business leaders
• Five practical steps companies can take now to prepare for AI-driven cyber threats
• Why reducing your internet-facing attack surface should be a priority
• How AI is changing the timeline between software patches and active exploitation
• Why organizations may need to rethink traditional patching schedules
• How legacy systems can create hidden vulnerabilities and what to do about them
• Why keeping decades of unnecessary data can dramatically increase the impact of a breach
• How honeypots and early detection can help reduce attacker dwell time
• Why traditional “gotcha” phishing tests can undermine employee trust and engagement
• How positive reinforcement can create stronger, longer-lasting cybersecurity behaviors
• Why psychological safety matters when employees make security mistakes
• How AI-powered phishing is making personalized social engineering more convincing
• What IT leaders should prioritize this quarter to prepare for the changing threat landscape
• Why cybersecurity resilience requires both stronger technology and better-equipped people

What if the IT provider you trust isn’t actually the problem—but the way IT support is structured is setting your company up to stay reactive?

In this episode of Between Fires and Futures, Tonya sits down with Scott Raymer, founder of Get It Sense, to unpack why so many IT departments and managed service providers are stuck in constant firefighting mode—and what business and IT leaders should be looking for if they want to move from reactive support to proactive IT management.

With more than two decades of experience consulting businesses on their technology needs, Scott explains why today’s IT challenges often come down to three critical areas: people, products, and processes. As cybersecurity threats, compliance requirements, data privacy concerns, and emerging technologies continue to evolve, the old “set it and forget it” approach to managed IT simply isn’t enough. Companies need clearly defined responsibilities, the right technology, proactive oversight, and providers willing to be held accountable for the service they promise.

Scott also breaks down what leaders should demand before signing an IT contract, including clearly defined service level agreements, response and restoration expectations, escalation paths, reporting, and a regular cadence of strategic reviews. He explains why organizations shouldn’t assume they are secure simply because nothing has gone wrong yet—and why factual, current assessments are essential for uncovering the invisible risks that could lead to downtime, ransomware, compliance issues, or costly business disruption.

They also explore how companies can strengthen an existing IT relationship without necessarily replacing a trusted provider, why cybersecurity and compliance require deeper expertise than many smaller IT teams can provide alone, and how emerging technologies like AI are making continuous education and modernization even more important. Scott shares why the IT solution that works today may not be enough six months from now—and what leaders can do to make sure their technology partners are prepared to evolve with them.

Tune in to hear:

• Why so many IT departments are stuck in reactive firefighting mode
• The three gaps behind many IT support problems: people, products, and processes
• Why the traditional “set it and forget it” MSP model no longer works
• How invisible cybersecurity and compliance risks can become expensive business disruptions
• What IT leaders should demand in writing from their service providers
• Why clearly defined SLAs, escalation paths, and accountability matter
• The red flags to watch for when evaluating a new IT provider
• How to strengthen a trusted IT relationship when your current provider lacks depth
• Why leaders need current, factual data before assuming their IT environment is secure
• How AI and other emerging technologies are changing what companies need from their IT partners

Important Links:

https://www.getitsense.com/

What happens when the cost of artificial intelligence keeps dropping, but your company’s AI bill keeps climbing?

In this season three premiere of Between Fires and Futures, Tonya sits down once again with Alan Clingerman, Chief Technology Strategist and Partner AI Officer at Dell Technologies, to unpack the rapidly changing economics of enterprise AI and what IT leaders need to understand as they plan for the future.

Alan explains why cheaper AI tokens aren’t necessarily translating into cheaper AI deployments. Longer context windows, agentic AI, data processing, cloud infrastructure, and increasingly complex workloads are creating costs that many organizations never anticipated. He also shares why companies that began experimenting with AI in the public cloud are now reconsidering where their workloads should live as those experiments move into production and scale.

They also dive into the growing shift toward edge, core, and cloud strategies, why AI PCs could fundamentally change the economics of AI adoption, and how specialized models and intelligent AI routing may help organizations control costs without sacrificing performance. Alan also explains why getting your data architecture right remains one of the most important steps companies can take as they prepare for a future driven by agents.

Tune in to hear:

• Why AI bills are rising even as token costs fall
• How AI agents dramatically increase token consumption
• The hidden costs behind enterprise AI deployments
• Why scaling cloud-based AI can create unexpected costs
• How to decide where AI workloads should run across edge, core, and cloud
• Why AI PCs could change the economics of AI adoption
• Why more organizations are bringing AI workloads back on-premise
• How smaller, specialized models can improve cost and performance
• Why data readiness is essential for successful agentic AI
• The three moves mid-market IT leaders should make right now

Important Links:

https://app.technologymatch.com/solutions/dell-technologies-ai-factory

https://app.technologymatch.com/solutions/dell-ai-pcs

https://app.technologymatch.com/solutions/dell-ai-solutions

https://app.technologymatch.com/solutions/dell-pro-ai-studio

https://app.technologymatch.com/solutions/dell-pro-max-with-gb10

https://www.linkedin.com/in/clingerman/

What if the technology decision that saved your company money three years ago is the very thing slowing your growth today?

In this season two finale of Between Fires and Futures, Tonya sits with Corey Wisdon to unpack one of the biggest hidden problems in mid-market IT: the long-term cost of “cheap and fast” infrastructure decisions.

Corey shares the story of a $3 million enterprise deployment that took eight months before users could even log in, and how that experience completely changed the way he approaches IT strategy, ServiceNow implementations, and AI adoption today. 

They also dive into the surprising reality behind enterprise deployments, the burnout happening on service desks, and why simplicity, integration, and long-term thinking matter more than ever in 2026.

Tune in to hear:

•  Why the “fast and cheap” IT decision often becomes the most expensive one later 
•  The hidden costs of fragmented tool stacks and over-customized platforms 
•  What really causes enterprise deployments to stall after go-live 
•  Why many organizations are failing to see ROI from AI tools 
•  The biggest mistakes companies make when rolling out AI internally 
•  How poor governance creates “agent sprawl” inside organizations 
•  Why mid-market companies are underserved by enterprise IT vendors 
•  The difference between ticketing systems and scalable enterprise platforms 
•  How RL Canning’s hosted ServiceNow model gets organizations live in just 45 days 
•  The importance of roadmap thinking instead of reactive technology purchases 
•  Why simplicity is becoming the most important strategy in modern IT

Connect with Corey: 

• https://www.linkedin.com/in/corey-wisdom-553a1611/
• https://www.linkedin.com/company/rl-canning/
• https://app.technologymatch.com/solutions/servicenow

AI is moving fast, but most leaders aren’t talking enough about the human side of what this moment is actually creating inside organizations: fear, uncertainty, imposter syndrome, and the pressure to adapt in real time. 

In this conversation, Tonya sits down with leadership coach and business strategist Raheela Nanji to unpack what leadership really looks like in the AI era and why the biggest challenge organizations face right now isn’t the technology itself. It’s how leaders guide people through the uncertainty surrounding it.

Drawing on more than 25 years of experience across technology, marketing, and business leadership, Raheela shares what she’s seeing behind the scenes inside organizations navigating AI adoption, from confusion and panic to innovation and possibility. Together, they explore why psychological safety, empathy, curiosity, and communication are becoming the most important leadership skills in modern business. 

In this episode, they explore:

•  Why AI is reshaping jobs rather than simply replacing them 
•  The hidden fear, uncertainty, and imposter syndrome leaders aren’t openly discussing 
•  Why psychological safety matters more than ever inside organizations 
•  How leaders can communicate AI initiatives without creating panic or resistance 
•  The danger of relying on AI without critical thinking and human oversight 
•  Why curiosity and empathy are becoming essential leadership skills in the AI era 
•  What organizations are getting wrong with AI spending and strategy 
•  How companies are using AI to scale knowledge, systems, and decision-making 
•  Why vulnerability and transparency build stronger leadership trust during uncertainty 
•  How AI is exposing leadership gaps that already existed beneath the surface 
•  The importance of helping teams adapt instead of pretending leaders have all the answers 
•  What separates organizations that will successfully evolve with AI from those that fall behind

Connect with Raheela:

https://www.linkedin.com/in/raheelananji/

https://ree-consulting.com/

AI is accelerating cybersecurity threats faster than most organizations are prepared for, and this episode will challenge the way you think about security, visibility, and prevention in the age of AI.

In this conversation, Tonya sits down with cybersecurity strategist John Fraser to unpack how AI is exposing security gaps inside organizations and why traditional “detect and respond” models are no longer enough. With experience spanning Department of Defense programs, enterprise IT environments, and high growth SaaS ecosystems, John brings a practical perspective on what’s actually happening inside modern security teams and where companies are falling behind.

In this episode, they explore:

•  Why AI is exposing security gaps most organizations don’t even realize they have 
•  How rogue AI usage inside companies is creating massive risk 
•  What happens when employees upload company data into LLMs and AI tools 
•  Why “detect and respond” security models are struggling to keep up 
•  How ransomware attacks have accelerated from days to minutes 
•  The real reason security teams are overwhelmed with alerts 
•  How AI is lowering the barrier to entry for cybercrime 
•  Why attackers are using AI to scale malware and phishing attacks 
•  The hidden risks of AI coding tools and copilots 
•  Where traditional zero trust security approaches fall short 
•  Why VPNs create dangerous visibility blind spots 
•  What organizations are missing when it comes to cloud security visibility 
•  The difference between reactive security and preemptive threat prevention 
•  Why visibility into network traffic matters more than ever 
•  What modern inline threat prevention looks like in practice 
•  How organizations can reduce alert fatigue and SOC overload 
•  Why companies need to treat AI as both a productivity tool and a security threat 
•  What separates organizations that adapt from those that fall behind in the AI era 

Connect with John:

[email protected] 

If flexible work feels like the future but your infrastructure still feels stuck in the past, this episode is going to challenge how you think about connectivity, security, and control.

In this conversation, Tonya sits down with Jess Jorgensen, founder and CEO of Go Roam Tech and Blush Technology Group, to unpack what’s really happening as work becomes untethered from place. From RVs and remote canyons to enterprise environments, Jess shares what breaks when people move faster than infrastructure and why most organizations are still operating on systems that were never designed for this reality.

They dive into the hidden risks of distributed work, the growing gap between IT responsibility and control, and what it actually takes to support a workforce that can log in from anywhere. Jess brings a rare, real world perspective from living and working fully remote, showing how the same foundational principles apply whether you’re running an enterprise network or working from the road.

This episode is a practical and eye opening look at what it means to build infrastructure that moves with your business and why the future of IT starts at the edge.

In this episode, they explore:

• Why flexible work is already happening with or without company approval
• Where infrastructure actually breaks in remote and hybrid environments
• The hidden risks of patchwork systems built during COVID
• Why one internet connection is effectively zero in a remote world
• How security gaps are expanding as employees work from uncontrolled environments
• What IT leaders are underestimating when it comes to AI and remote access
• Why shadow IT and unauthorized tools are accelerating risk
• The real reason remote work is now a talent acquisition and retention strategy
• How poor user experience drives employees to create risky workarounds
• What it takes to create secure, always on connectivity anywhere
• Why IT must shift from control to enablement in a decentralized world
• How to rethink your tech stack for the next 12 to 18 months

Important Links:

https://app.technologymatch.com/solutions/working-from-roam

https://app.technologymatch.com/solutions/advisory-services-1

If AI feels like the right move but you’re still not seeing results, this episode reframes where the real problem is.

In this conversation, Tonya sits down with Ray LaMarca, Director of Solutions Engineering at NetApp, to unpack why most AI initiatives stall out before they ever deliver value. It’s not the tools. It’s the foundation underneath them.

They break down what’s actually going wrong behind the scenes, from siloed data and security risks to misalignment between business and IT. Ray shares what he’s seeing across enterprise teams, where companies are overspending, and why ROI is taking longer than expected.

This episode is a grounded look at what it really takes to turn AI from an experiment into a strategic advantage and why it all starts with your data.

In this episode, they explore:

• Why most AI projects fail before they ever reach production and what’s really causing it
• The hidden breakdown between business and IT and how it impacts results
• Why data security is still the number one concern for IT leaders in the AI era
• How siloed data systems create inefficiencies, risk, and missed opportunities
• What actually happens when your data isn’t clean, complete, or protected
• Why massive investments in GPUs and cloud infrastructure aren’t delivering ROI
• The real reason companies are slow to see value from AI initiatives
• How supply chain, timing, and misaligned investments derail outcomes
• Why asking better questions is the fastest way to avoid failure
• What it means for IT to shift from cost center to revenue driver
• How partnerships, not just products, determine success in modern IT strategy
• Real world examples of companies using AI and data to drive efficiency and innovation
• What IT leaders should prioritize over the next 12 to 18 months to stay competitive

Important Links:

https://app.technologymatch.com/solutions/netapp-ai-data-engine

https://app.technologymatch.com/solutions/netapp-afx

If AI feels like the biggest opportunity (and risk) in your business right now, this episode reframes the conversation in a way most leaders are missing: it’s not an AI problem, it’s a data problem—and more importantly, it’s a thinking problem.

In this conversation, Tonya sits down with Richard Walker, founder and CEO of Quick, to unpack what’s really driving outcomes in the AI era. Drawing on decades of experience structuring and scaling data across millions of forms, Richard challenges the default way most companies approach AI—as a tool—and introduces a far more powerful lens: AI as a coworker.

They explore why everyone has access to the same models, but vastly different results, and how the real differentiator lies in how you think, plan, and interact with AI. From treating AI like a human collaborator to building panels of experts and defining “mental models,” this episode offers a practical and deeply strategic framework for leaders navigating what’s next.

Richard also shares how his team is leveraging unique data sets to build entirely new capabilities, why most organizations are sitting on untapped data goldmines, and what it actually takes to move from experimentation to operational impact.

This conversation is a masterclass in slowing down to move faster—reframing AI from a speed tool into a strategic advantage that compounds across your business.

In this episode, they explore:

• Why most companies don’t have an AI problem—they have a data problem
• How treating AI like a coworker changes the quality of your results
• The concept of “toddler syndrome” and why AI can feel both brilliant and unpredictable
• Why prompting is less important than problem clarity and structured thinking
• How to use AI to write better prompts than you ever could yourself
• The power of “mental models” and how they shape AI behavior and outputs
• Why planning upfront eliminates endless iteration and rework
• How different AI models vary in strengths (and how to use them together)
• The concept of building a “panel of experts” to solve complex problems
• Why unique data—not AI access—is the true competitive advantage
• How companies are sitting on untapped data that can unlock new products and revenue streams
• The importance of enriching and structuring data before applying AI
• Why adoption is a leadership problem—and how to drive it inside your organization
• How AI is shifting roles from execution to orchestration and strategic thinking
• What the future of leadership looks like when managing both human and AI teams

Important Links:

https://app.technologymatch.com/solutions/quik-api

If telecom sits underneath everything in your business but rarely gets attention, this episode pulls back the curtain on why that invisibility is exactly where cost, inefficiency, and risk quietly accumulate.

In this conversation, Tonya sits down with Stephen Hancock, founder and president of Socium IT, to unpack why telecom is one of the most overlooked (and under-optimized) layers inside IT. They explore how unmanaged vendor ecosystems, lack of visibility, and outdated documentation create compounding inefficiencies and why most organizations don’t realize the scale of the problem until they audit it. 

Stephen shares how telecom has quietly evolved into a utility—critical, but often ignored—and why treating it that way without operational discipline leads to wasted spend, lost time, and missed strategic opportunities. From invoice complexity to contract sprawl, this conversation reframes telecom as a lever for both cost recovery and organizational leverage. 

He also breaks down how AI is reshaping vendor evaluation and telecom management, where it creates leverage (and where it creates risk), and why the future of IT leadership requires both financial clarity and operational ownership across the full lifecycle. This episode offers a practical lens on how to reclaim control, reduce noise, and redirect resources toward higher-value initiatives like AI, security, and innovation. 

In this episode, they explore:

• Why telecom is one of the least visible, but most impactful, layers in IT 
• How small operational tasks quietly compound into major time and cost drains 
• Where organizations lose the most money (and time) in telecom management 
• The hidden risks of invoice complexity, billing errors, and contract auto-renewals 
• Why lack of inventory and documentation creates ongoing inefficiency 
• How telecom overspend often happens without anyone noticing 
• The concept of telecom as a “utility” and what that means for IT strategy 
• How AI is changing vendor evaluation and where it can create overconfidence 
• Why advisory alone is no longer enough without execution and lifecycle ownership 
• The disconnect between tools, data, and true operational accountability 
• How IT leaders can align more effectively with CFOs using financial clarity 
• The importance of establishing a clean baseline before making technology decisions 
• Where leaders should reinvest reclaimed time and budget (AI, security, innovation) 
• The single highest-leverage step IT leaders can take right now: building inventory visibility

Important Links:

https://app.technologymatch.com/solutions/telecom-contract-negotiation-rate-benchmarking

https://app.technologymatch.com/solutions/telecom-cost-optimization-for-multi-location-enterprises

https://app.technologymatch.com/solutions/telecom-expense-management-1