Tech Talks Daily

What happens when your customers stop searching through pages of Google results and start asking ChatGPT, Claude, and other AI platforms which companies they should trust?
In this episode of Tech Talks Daily, I speak with Kathleen Lucente, founder and CEO of Red Fan Communications, about zero-click search, AI-mediated discovery, and why producing more content is unlikely to solve the growing challenge of brand visibility in AI-generated answers.
Kathleen argues that content is what a company says about itself, while authority is built through what credible third parties say about it. As buyers increasingly use large language models to research companies, compare vendors, and make purchasing decisions, earned media, analyst relations, customer reviews, executive visibility, original research, and consistent brand messaging are becoming increasingly important signals of trust.
But building brand authority cannot be completed in a few weeks or solved by purchasing another AI visibility tool.
Kathleen explains why companies appearing prominently in AI-generated answers often earned that position through years of reputation building. We discuss her seven-part framework for measuring brand authority across earned media, company recognition, reviews, entity coherence, content authority, social authority, and technical readiness, as well as how marketing leaders can identify where their companies are falling behind competitors.
The conversation also examines what the rise of generative engine optimization, answer engine optimization, and AI search means for traditional SEO and content marketing strategies. Kathleen explains why SEO still matters but can no longer carry the entire burden of brand discovery, and why marketing, communications, sales, customer success, and executive leadership must work together to build the credibility signals that influence both people and AI systems.
We also discuss how companies can measure reputation and connect communications programs to tangible business outcomes. Kathleen shares examples of original research and earned media opening doors to new customers, generating conversations with major publications, and creating commercial opportunities that traditional sales efforts had struggled to reach.
Drawing on more than 30 years of experience helping B2B technology companies through IPOs, acquisitions, funding rounds, and periods of rapid growth, Kathleen explains why reputation often acts as invisible insurance for a business. Companies may not recognize its value until a deal, crisis, leadership change, or major transaction puts trust under pressure.
Finally, Kathleen shares practical advice for B2B technology leaders who want their companies to become trusted authorities in the age of AI search. From auditing how your brand appears across multiple sources to refreshing customer reviews, developing credible executive voices, strengthening analyst relationships, and creating original data that journalists and industry leaders want to reference, this conversation offers a practical roadmap for companies trying to become visible in AI-generated answers.
Is your company still trying to win the AI search battle by producing more content, or are you investing in the reputation and third-party credibility that will influence how both people and AI systems perceive your brand? Share your thoughts with me.

What happens when an industry managing more than $150 trillion is still held back by decades-old systems, manual work, disconnected data, and highly paid experts spending hours on tasks AI could complete in seconds?
In this episode, I speak with Markus Ruetimann, a member of the Experion Technologies Advisory Board and former Global Chief Operating Officer with more than three decades of experience in institutional asset management, alongside Siraj Alimohamed, Global Head of Data and AI at Experion Technologies.
We begin with a simple question. What does an asset manager actually do with our pensions, savings, and investments every day? Markus takes us through the investment process, from research and stock selection to portfolio construction, trading, settlement, performance analysis, and regulatory reporting. Along the way, we examine where time, money, and expertise are being lost.
Siraj then explains composable AI through one of the clearest analogies I have heard. Think of building with Lego bricks rather than creating every solution from scratch. Companies can create reusable AI agents for research, risk monitoring, compliance, portfolio analysis, trade execution, and reporting, all operating on a shared data and governance foundation.
We discuss how this model can change the economics of AI adoption. Siraj shares examples of AI reading hundreds of broker reports in seconds, freeing hundreds of analyst hours, reducing portfolio review cycles from days to hours, improving trade execution quality, identifying settlement risks before trades fail, and accelerating regulatory reporting.
The conversation also tackles one of the most common reasons companies delay AI projects: "our data isn't ready." Siraj argues that waiting for perfect data can become an excuse for inaction. His advice is to identify two or three measurable use cases, prove their value within weeks, and use those results to build confidence and secure further investment.
But technology is only part of the story. Markus explains why AI adoption in asset management is also a cultural and organizational challenge. Companies must decide which processes to automate, which to support with AI, and where human judgment must remain firmly in control.
The message from both guests is refreshingly practical. Start small, start with a real business problem, connect AI systems through a common data foundation, and give skilled people more time to make better decisions.
Can composable AI help asset managers respond faster, reduce costs, improve investor returns, and make better use of human expertise, or will legacy systems and cultural resistance continue to slow progress? Listen to the conversation and share your thoughts.

Have you ever wondered whether the biggest competitive advantage in wealth management is no longer investment performance alone, but the ability to turn information into action faster than everyone else?
In this episode of Tech Talks Daily, I welcome Bob Pisani, Chief Technology Officer at Addepar, a platform that helps investment professionals manage and analyze more than $9 trillion in assets globally. Our conversation explores why modern wealth management has become a technology challenge just as much as a financial one, and why firms that continue relying on fragmented legacy systems risk falling behind in an industry where speed, data quality, and client expectations are changing faster than ever.
Bob explains how wealth advisors have historically spent far too much of their day moving between disconnected systems, stitching together spreadsheets, and trying to answer client questions using incomplete information. While that may once have been acceptable, today's investors expect near real-time visibility into their portfolios, along with personalized guidance that reflects rapidly changing market conditions. That changing expectation places an enormous premium on time, making technology one of an advisor's most valuable assets.
Our discussion explores why successful AI initiatives begin long before deploying a model. Data quality, governance, and creating a trusted source of truth remain the foundations that determine whether AI produces reliable insights or simply accelerates poor decisions. Bob shares how Addepar approaches this challenge by bringing together fragmented financial data, standardizing it across hundreds of custodians, and creating the conditions where AI can produce meaningful, actionable intelligence rather than more noise.
We also look at practical examples of AI already improving advisor productivity today. From summarizing portfolio performance and analyzing complex alternative investment documents to introducing intelligent agents that reduce operational workload, Bob explains how AI is freeing experienced professionals to spend less time gathering information and more time building trusted client relationships.
One of my favorite moments in our conversation comes when we discuss predictive intelligence. Instead of waiting for advisors to search for answers, AI is beginning to surface opportunities, risks, and client conversations before anyone even knows which questions to ask. That represents a fundamental change in how financial advice can be delivered, moving from reactive reporting toward proactive guidance that is grounded in trusted data.
We also address one of the biggest questions surrounding AI in financial services. Will technology replace human advisors? Bob offers a thoughtful perspective, arguing that while AI can automate repetitive work and accelerate decision-making, qualities such as judgment, precision, trust, and human relationships remain impossible to automate. Those are the characteristics clients ultimately value most when making important financial decisions.
As our conversation draws to a close, Bob shares why he believes the gap between firms embracing AI and those delaying modernization will widen rapidly. The organizations investing today in clean data, modern platforms, and AI-ready operations will be better positioned to serve clients, attract talent, and compete in an increasingly fast-moving market.
Can wealth management continue to rely on yesterday's technology in an AI-driven world? And if time has become the industry's most valuable asset, how is your business making the most of it? I'd love to hear your thoughts after listening.

Have you ever stopped to think about what really powers the AI revolution? While the conversation often focuses on the latest models, chips, and applications, the real story may lie in something far less visible: the energy systems and digital architecture that make it all possible.
In this episode of Tech Talks Daily, I welcome Sadiq Syed, Senior Vice President of Digital Energy Software at Schneider Electric, to discuss why the future of electrification depends as much on software as it does on hardware. As demand for AI continues to grow at an extraordinary pace, data centers are consuming increasing amounts of electricity, putting pressure on aging grids and exposing the limitations of traditional approaches to energy management.
During our conversation, Sadiq explains why electrification alone cannot deliver global decarbonization goals. Without intelligent software capable of monitoring, predicting, and optimizing energy usage, businesses risk wasting valuable resources while struggling to meet rising demand. We discuss why AI may ultimately become the technology that helps solve the energy challenges it has helped create, using continuous analytics and predictive intelligence to improve efficiency across complex environments.
We also examine the growing regulatory pressure. With more than a thousand energy-related regulations introduced around the world in recent years, compliance has become part of everyday operations rather than an occasional reporting exercise. Sadiq explains why organizations should stop viewing compliance as an administrative burden and instead see it as an opportunity to build trust, strengthen resilience, and improve operational performance.
Another area we explore is digital resilience. Whether supporting hospitals, pharmaceutical manufacturers, or mission-critical data centers, modern infrastructure depends on uninterrupted operations. Sadiq shares why cybersecurity, predictive maintenance, unified operational visibility, and connected digital platforms are becoming central to maintaining uptime while helping organizations make better use of limited energy resources.
The conversation also turns to people. As experienced engineers retire and younger generations enter the workforce with very different expectations, organizations face an urgent challenge: modernizing the tools they provide. We discuss how intuitive digital platforms can reduce complexity, shorten training time, attract the next generation of technical talent, and make daily operations easier to manage.
Throughout our discussion, one message remains consistent. The future of sustainable infrastructure is built on the combination of electrification, automation, and intelligent software. From AI-enabled operational insights to connected energy management platforms, technology is becoming the foundation that allows businesses to balance performance, sustainability, regulatory requirements, and resilience in an increasingly unpredictable world.
Is the biggest challenge facing AI actually an energy challenge? And if software is becoming the foundation for modern electrification, how prepared is your organization for what comes next? I'd love to hear your thoughts after listening.

How is AI changing the way we choose hotels, and what does that mean for the businesses trying to deliver unforgettable guest experiences?
In this episode, I speak with Frank Pitsikalis, Senior Vice President of Product Strategy and Chief Marketing Officer at Agilysys, about how AI is changing hospitality from the very first search through to every interaction a guest has during their stay.
Travel planning is already changing. More travelers are turning to AI assistants instead of traditional search engines or online travel agencies, asking detailed questions about destinations, dining, activities, and experiences. That creates both an opportunity and a challenge for hotels. If AI is recommending experiences rather than simply rooms, hospitality businesses need technology behind the scenes that can actually deliver on those promises.
Frank explains why connected systems have become the foundation for modern hospitality. For many years, hotels invested in individual systems for reservations, restaurants, spas, golf courses, and guest services. While each application may have worked well on its own, they often failed to share information in meaningful ways. As AI becomes more capable, those disconnected systems become increasingly difficult to work around.
We also explore how leading hospitality brands are changing the way they measure success. Rather than focusing solely on room occupancy, many are now looking at total guest spend across dining, wellness, entertainment, and other services. Frank explains how better use of guest data helps properties create more personalized experiences while also improving operational performance and profitability.
Another fascinating part of our discussion centers on personalization. We talk about what genuine one-to-one guest experiences look like when AI helps staff understand preferences, dietary requirements, previous visits, and even customer sentiment before every interaction. Rather than replacing hospitality professionals, AI is giving them the information they need to create memorable experiences that feel thoughtful and genuinely personal.
Throughout our conversation, Frank returns to a simple but powerful idea. Technology works best when it disappears into the background, allowing people to focus on serving people. AI may be changing how guests discover, book, and experience travel, but hospitality will always be judged by how people are made to feel.
If you work in hospitality, customer experience, or enterprise technology, this conversation offers a practical look at how connected data, AI, and operational excellence are coming together to redefine the guest journey.
As AI becomes part of every stage of travel, is your business building the connected experiences that today's guests increasingly expect?