How can companies invest heavily in AI and still struggle to see meaningful returns?

In this episode of Tech Talks Daily, I sit down with Thomas Scott, CEO of Wrike, to unpack a growing tension many organizations are facing right now.

Artificial intelligence adoption is accelerating rapidly across the workplace, yet the structures needed to support it are struggling to keep pace. Wrike's latest research into the "Age of Connected Intelligence" reveals that more than 80 percent of employees are already using AI at work. Yet fewer than half have received any formal training, guidance, or governance around how these tools should be used.

That gap between enthusiasm and enablement is creating a new workplace phenomenon that many leaders are only just beginning to notice.

Shadow AI. When employees cannot find approved tools that solve their problems quickly, they often turn to unapproved applications or personal accounts instead. Wrike's data shows that 42 percent of workers admit they have already done this. For organizations handling sensitive data, intellectual property, or regulated information, that trend raises serious questions about security, compliance, and trust.

Thomas explains why this pattern is not surprising. Whenever a new technology emerges, the builders and experimenters move first. They explore possibilities, test new tools, and discover productivity gains long before formal policies or training frameworks arrive. The challenge for leadership teams is learning how to harness that momentum without letting experimentation turn into fragmentation.

We also explore one of the most overlooked barriers to AI return on investment. Integration. Many employees are now juggling multiple AI tools every week, yet those systems rarely communicate with one another or connect deeply into the core business platforms where real work happens. As a result, context gets lost, workflows become fragmented, and organizations end up running expensive pilots that never scale into meaningful transformation.

Thomas introduces the idea of connected intelligence as a possible solution. Instead of deploying AI tools in isolation, companies need systems that understand context across projects, teams, and workflows. When AI can access structured data, shared history, and operational context, it becomes far more capable of supporting real decision making rather than simply generating isolated outputs.

Our conversation also explores how leaders can move beyond scattered experimentation and start building structured AI adoption across their organizations.

Thomas argues that the most successful companies start with highly specific problems, empower small groups of motivated builders, and maintain strong executive involvement throughout the process. AI transformation is rarely driven by technology alone. It requires people, process, and leadership alignment working together.

So if your organization has already deployed AI tools but still struggles to see real impact, perhaps the question is not whether you are using AI. The real question might be whether those tools are truly connected to the work your teams are trying to do every day.

How can organizations use AI to transform hiring while still protecting the human element at the heart of work?

In this episode of Tech Talks Daily, I sit down with Mahe Bayireddi, co-founder and CEO of Phenom, to explore how artificial intelligence is reshaping the way companies attract, hire, and develop talent.

Our conversation comes at an interesting moment for the company, following the announcement that Phenom has acquired Be Applied, an AI-driven cognitive assessment platform designed to validate candidate and employee capabilities at scale. The move follows an earlier acquisition of Included, an AI-native people analytics platform focused on delivering deeper workforce insights and faster decision making.

Mahe shares how Phenom's long-term mission to help a billion people find the right job is evolving as AI becomes embedded throughout the HR lifecycle. From candidate discovery to onboarding and internal mobility, organizations are now experimenting with automation, personalization, and intelligent workflows that aim to improve both productivity and employee experience.

One theme that runs throughout our discussion is how AI adoption in HR varies dramatically depending on geography, regulation, and industry. In Europe, regulatory frameworks are shaping how companies deploy automation. In the United States, state-level policies introduce additional complexity. Meanwhile, organizations across Asia are often approaching AI with entirely different priorities. As a result, many global companies are experimenting carefully, introducing AI into specific business units or regions before rolling it out more broadly.

We also talk about a challenge that has caught many HR teams by surprise: the growing issue of fraudulent candidates and identity manipulation in the hiring process. As job applications become easier to submit and remote work expands global talent pools, organizations must rethink how they validate candidate identity and credentials. Mahe explains how AI-driven fraud detection tools can help highlight suspicious patterns while still keeping humans in the loop for final decisions.

Another important point raised in the conversation is the need to preserve humanity in the workplace while introducing intelligent automation. While AI can dramatically improve efficiency across recruiting and workforce planning, Mahe believes HR leaders must be careful to ensure technology strengthens human potential rather than reducing people to data points in a system.

Looking ahead, we discuss how organizations can begin adopting AI responsibly by starting small, focusing on high-impact areas, and building guardrails that reflect regional regulations and company culture. For many companies, the most successful path forward will involve testing AI within specific workflows, measuring outcomes quickly, and scaling what works.

So as artificial intelligence becomes a central part of hiring, workforce planning, and employee development, the big question for leaders is this. Can organizations use AI to create faster, smarter talent decisions while still keeping people at the center of the workplace experience?

How does a CISO turn cybersecurity from a technical conversation into a business conversation that boards actually care about?

In this episode of Tech Talks Daily, I sit down with Thom Langford, EMEA CTO at Rapid7 and a former CISO, to explore what he calls the second phase of cybersecurity leadership. For years, the industry worked hard to secure a seat at the boardroom table. In many organizations, that mission has largely succeeded. But as Thom explains, gaining access was only the first step. The real challenge now is communicating security in a way that drives meaningful business decisions.

Thom shares why many CISOs still approach board conversations in the same way they did a decade ago, even though boardroom awareness of cybersecurity has changed dramatically. Today, many boards include members with cybersecurity knowledge or direct security experience. That means security leaders can no longer rely on technical jargon, complex frameworks, or compliance language to make their case.

One of the most interesting insights from our conversation is the disconnect between how CISOs frame risk and what boards are actually focused on. While security teams often lead with risk reduction, boards tend to think in terms of revenue growth and operational costs. Thom argues that security leaders must learn to translate cybersecurity into the language of profit and loss if they want their message to resonate at the executive level.

We also explore how traditional security tools such as risk frameworks, audits, and compliance standards can sometimes create distance rather than clarity in board discussions. Instead of helping executives understand security priorities, these models can obscure the real question boards are trying to answer. How secure are we, and what does that mean for the business?

Another area we discuss is the growing role of tabletop exercises. Thom explains why these simulations are becoming one of the most effective ways for CISOs to demonstrate the real-world impact of security decisions. By walking executives through a realistic incident scenario, leaders can see how security, operations, legal teams, and business priorities intersect during a crisis.

Looking ahead, Thom believes the most successful CISOs will increasingly need to think like business leaders rather than purely technical specialists. Communication skills, relationship building, and understanding the organization's financial priorities may prove just as important as deep technical expertise.

So if cybersecurity leaders have already earned their place in the boardroom, the next question becomes much more interesting. Are they speaking the language the board actually understands, or are they still trying to solve business problems using only security vocabulary?