Google AI Mode - More than just a new way to search for information

Google AI Mode is here in the UK and it’s not just another incremental update to Google's search algorithm.  This is a complete reimagining of what it means to search for information in the age of AI.

In this episode of the Inspiring Tech Leaders podcast, I explore the following:

💡 The technology powering AI Mode 

💡 Real business impact on publishers and creators 

💡 Regulatory challenges across different markets 

💡 What this means for the future of information access

Listen to the full analysis and discover what this means for your digital strategy.

What's your take?  Are you excited about AI-powered search or concerned about its impact on the web ecosystem?

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Chapters

• 0:00 Introduction
• 1:58 What is Google AI Mode?
• 4:53 The Google AI timeline of events
• 9:15 The controversy surrounding Google AI Mode
• 15:04 The AI Engine behind AI Mode
• 19:32 [Ad] Crossing Borders
• 20:10 (Cont.) The AI Engine behind AI Mode
• 21:28 Potential pushback on Google AI Mode
• 26:43 A new information landscape
• 32:46 Wrap up

Transcript

Welcome to the Inspiring Tech Leaders podcast, with me Dave Roberts.  This is the podcast that talks with tech leaders from across the industry, exploring their insights, sharing their experiences, and offering valuable advice to technology professionals.  The podcast also explores technology innovations and the evolving tech landscape, providing listeners with actionable guidance and inspiration.

Today I am going to talk about a new Google feature, which has recently been rolled out to UK users and represents a major change in the way we search for information.  It's called Google AI Mode, and if you haven't heard of it yet, you will soon.  Because this isn't just another incremental update to Google's search algorithm. This is a complete reimagining of what it means to search for information in the age of AI.

Instead of typing a few keywords and getting a list of blue links to click through, you can now ask Google complex, multi-part questions in natural language and receive comprehensive, conversational answers powered by advanced AI.  Instead of conducting multiple searches and piecing together information from various websites, AI Mode can understand your entire question and provide a tailored response in seconds.

But here's where it gets interesting, and also somewhat controversial.  This shift toward AI-generated answers is already causing significant disruptions across the digital economy.  Major publishers are reporting traffic drops of up to 50 percent.  Content creators are questioning how they'll survive in a world where Google keeps users on its own pages rather than directing them to external websites.  And critics are raising serious concerns about accuracy, environmental impact, and the concentration of information power in the hands of a single company.

In this episode I will break down exactly what Google AI Mode is and how it works, examine the technology powering it, investigate the business implications that have publishers and content creators worried, and look at what this means for the future of how we discover and consume information online.

So, what exactly is Google AI Mode, and why is everyone talking about it?

To understand the significance of AI Mode, we first need to understand what it actually is and how it differs from the Google search we've all been using for decades.  Traditional Google search, the one we're all familiar with, works by matching your keywords to web pages and presenting you with a ranked list of results.  It's a system that has worked remarkably well for over 20 years, processing billions of queries every day and driving enormous amounts of traffic across the web.

AI Mode uses Google's most advanced artificial intelligence system, Gemini 2.5, to understand your question and generate a comprehensive, conversational response directly on Google's own page.  According to Google's official description, AI Mode is designed as "our most powerful AI search" that allows users to "ask whatever's on your mind to get an AI powered response and explore further with follow-up questions and helpful web links”.  The key difference is in that phrase "AI powered response".  Rather than directing you elsewhere for answers, Google is now positioning itself as the answer provider.

The technology behind AI Mode is very impressive. It uses what Google calls "advanced reasoning, thinking and multimodal capabilities" powered by the Gemini 2.5 model.  This means you can interact with it not just through text, but also through voice commands and by uploading images.  You could, for example, take a photo of a plant in your garden and ask AI to identify it and provide care instructions, all in a single, natural language query.

But perhaps the most significant technical innovation is something Google calls the "query fan-out technique”.  When you ask AI Mode a complex question, it doesn't just search for that exact phrase.  Instead, it breaks your question down into multiple sub-topics and conducts several related searches simultaneously across different data sources.  It then synthesises all of this information into a single, coherent response.

The system also includes a feature called Deep Search, which Google describes as "our most advanced research tool in Google Search”.  Deep Search can browse hundreds of websites and reason across them to create comprehensive, fully-cited reports in just minutes. However, this feature is currently only available to Google AI subscribers, indicating that Google sees premium AI search capabilities as a potential revenue stream.

Currently, AI Mode is available in the United States, India, and as of this week, the United Kingdom. It appears as both a tab option and within the search box itself, making it optional for users who prefer traditional search results. Google has been careful to position it as an addition to, rather than a replacement for, traditional search.

However, the company acknowledges that AI Mode is experimental and may make mistakes. This admission of fallibility is crucial because it highlights one of the central tensions in this new world of search, which is the trade-off between convenience and accuracy.

Now, the story of AI Mode's rollout reveals a lot about Google's strategy and the challenges of deploying advanced AI systems at global scale. This isn't a feature that appeared overnight. It's the result of careful, phased deployment that began in Google's home market and is now expanding internationally.

The timeline tells an interesting story. AI Mode first launched to users in the United States at the end of May 2025.  This initial rollout served as a real-world testing ground, allowing Google to gather user feedback and identify potential issues before expanding to other markets. The choice of the US as the first market makes sense from both a business and technical perspective.  As Google's largest market and home base, the US provided the ideal environment for initial deployment and iteration.

Following the US launch, Google expanded AI Mode into India in early July 2025. This choice is particularly strategic.  India represents one of the world's largest and fastest-growing internet markets, with a population that is increasingly mobile-first and comfortable with voice-based interactions.  The Indian market also presents unique linguistic and cultural challenges that help Google test AI Mode's capabilities across different languages and search patterns.

Now, as of start of August, AI Mode is rolling out to users in the United Kingdom. According to Google, the feature will appear as a tab on Google Search results pages and in the Google app for both Android and Apple smartphones, with full availability to all UK users expected over the next few days.

The phased rollout strategy reflects the complexity of deploying AI systems at Google's scale.  When you're processing billions of search queries every day, even small changes can have massive implications. By starting with smaller, controlled deployments, Google can monitor system performance, user behaviour, and potential unintended consequences before committing to global availability.

But there's another factor at play in this rollout strategy, which is regulatory considerations. Notably absent from the list of supported countries is the European Union.  Google explicitly states that AI Overviews, the precursor to AI Mode, is not available in the EU where legislation precludes it.  This is likely a reference to the EU's AI Act and other regulatory frameworks that impose strict requirements on AI systems, particularly those that could influence public opinion or access to information.

The user experience of AI Mode varies slightly depending on how you access it.  On desktop computers, AI Mode appears as a tab alongside traditional search options like "All," "Images," and "News”.  On mobile devices, it's integrated into the Google app with options to input queries through text, voice, or by uploading images.  This multimodal approach reflects Google's understanding that mobile users often prefer voice interactions and visual search capabilities.

Early user data suggests that AI Mode is changing how people formulate their search queries.  According to Google's vice president of product management for search, early users of AI Mode are asking questions that are two or three times the length of traditional search queries.  This shift toward longer, more conversational queries represents a fundamental change in how people interact with search engines.

The rollout has been accompanied by extensive user education efforts.  Google has created detailed help pages, video demonstrations, and blog posts explaining how to use AI Mode effectively.  This educational component is crucial because AI Mode requires users to think differently about search.  Instead of optimising for keywords, users need to learn to ask complete, natural language questions.

However, the rollout hasn't been without challenges.  Google acknowledges that AI Mode is experimental and may make mistakes.  The company has implemented several safeguards, including fallback mechanisms that provide traditional search results when the AI isn't confident in its response. There are also content filters and fact-checking systems designed to minimise the spread of misinformation, though critics argue these measures may not be sufficient.

The international expansion of AI Mode also raises questions about cultural and linguistic adaptation.  Search behaviour varies significantly across different cultures and languages. What works for English-speaking users in the US may not translate directly to users in India or the UK, let alone to future markets with different languages and cultural contexts.

Now we come to the heart of the controversy surrounding AI Mode, and it's here that we need to understand the profound economic implications of this technological shift.   What we're witnessing isn't just an evolution in search technology, it is actually a potential disruption of the entire digital economy that has been built around Google's traditional search model over the past two decades.

To understand the magnitude of this disruption, let's start with some interesting numbers. The Daily Mail, one of the UK's largest online news publishers, reports that the number of people clicking through to their website from Google search results has fallen by approximately 50 percent on both desktop and mobile traffic, since Google introduced its AI Overview feature, which is the precursor to AI Mode.  Let that sink in for a moment, a 50 percent reduction in one of the most important traffic sources for online publishers.

But the Daily Mail's experience isn't isolated.  A recent study by the Pew Research Center provides even more alarming statistics for content creators and publishers.  The research found that when users receive an AI summary at the top of their search results, they click on traditional search results almost 50 percent less frequently.

Even more concerning for publishers is what happens with the links that are included within AI summaries themselves.  The Pew study found that only 1 percent of users clicked on links provided within AI-generated responses.  This means that even when AI Mode includes citations and links to source material, users are overwhelmingly choosing to stay on Google's page rather than visiting the original sources.

To understand why this matters so much, we need to examine the economic model that has powered the web for the past two decades.  Google's traditional search has functioned as a massive traffic distribution system.  Publishers create content, Google indexes it and presents it in search results, users click through to publisher websites, and publishers monetize that traffic through advertising, subscriptions, or other revenue models.  This symbiotic relationship has supported everything from major news organisations to small niche blogs, creating a diverse ecosystem of online content.

AI Mode fundamentally disrupts this model by keeping users on Google's own pages. Instead of directing traffic to external websites, Google is now positioning itself as the destination for information, not just the directory.  This shift has profound implications for every business that relies on search traffic for revenue.

The implications extend far beyond just advertising revenue. Many businesses have built their entire digital strategies around search engine optimisation, content marketing, and organic search traffic.  E-commerce sites rely on Google to drive product discovery.  News organisations depend on search traffic to build their subscriber base.  Educational websites, recipe blogs, how-to guides, and countless other types of content creators have structured their businesses around the assumption that valuable content will be rewarded with search traffic.

Google's AI systems are trained on vast amounts of web content, much of it created by the same publishers and content creators who are now seeing their traffic decline.  There's an inherent tension in a model where Google uses content created by others to provide answers that keep users from visiting the original sources.

The scale of this potential disruption becomes clearer when we consider Google's current reach.  The company already generates more than two billion AI Overview boxes every day in more than 40 languages.  As AI Mode expands and becomes more sophisticated, this number is likely to grow exponentially.

Some publishers are already adapting their strategies in response to these changes. Some are focusing more heavily on direct traffic through newsletters and social media.  Others are exploring partnerships with AI companies or developing their own AI-powered tools.  But these adaptations require significant resources and may not be viable for smaller content creators.

The situation is further complicated by the fact that Google's AI systems rely on the very content ecosystem they may be disrupting.  If publishers and content creators can no longer sustain their operations due to reduced traffic, the quality and diversity of information available for AI training could decline over time.  This creates a potential feedback loop where the success of AI search could undermine the content ecosystem that makes it valuable.

There are also broader questions about information diversity and access.  When Google's AI provides a single, synthesised answer to complex questions, users may be less likely to encounter diverse perspectives or to engage in the kind of critical evaluation that comes from comparing multiple sites.  This could have implications for everything from political discourse to consumer decision-making.

The advertising implications are particularly complex.  Google's traditional search advertising model is based on users clicking through to advertiser websites.  If AI Mode keeps users on Google's pages, the company will need to develop new advertising formats and revenue-sharing models.  Some industry observers speculate that Google might introduce sponsored content within AI responses or develop new forms of native advertising integrated into AI-generated answers.

However, Google disputes some of the research methodology behind the traffic decline statistics.  The company argues that the Pew Research Center study was flawed and doesn't accurately represent real-world usage patterns.  Google maintains that AI features actually increase overall search engagement and lead to more diverse information-seeking behaviour.

Despite these disputes, the concerns are real enough that they're attracting attention from regulators and policymakers.  The concentration of information access in the hands of a single company raises antitrust questions, particularly in markets where Google already holds dominant positions in search and digital advertising.

To truly understand the implications of AI Mode, we need to look under the hood at the technology that makes it possible.  What we're dealing with here isn't just a simple chatbot or a more sophisticated search algorithm.  AI Mode represents the deployment of some of the most advanced artificial intelligence systems ever created, operating at a scale that few organisations in the world could manage.

At the core of AI Mode is Google's Gemini 2.5 model, which represents the latest generation of large language models. These systems are trained on vast datasets that include much of the publicly available text on the internet, along with books, academic papers, and other sources of human knowledge. The scale of this training is almost incomprehensible, as we're talking about hundreds of billions of parameters and training datasets that include trillions of words.

It works in a way that when you ask AI Mode a complex question, the system doesn't just search for that exact phrase. Instead, it uses advanced natural language processing to understand the intent and components of your question.  It then breaks that question down into multiple sub-topics and generates several related search queries automatically.  These queries are executed simultaneously across multiple data sources, and the results are then synthesised using the AI model's reasoning capabilities to create a coherent, comprehensive response.

The multimodal capabilities add another layer of complexity. AI Mode can process not just text queries, but also voice commands and uploaded images.  The image processing uses computer vision models that can identify objects, read text, and understand spatial relationships. 

However, this technological sophistication comes with significant challenges, particularly around accuracy and reliability. Google acknowledges that AI Mode may make mistakes, and this isn't just a minor disclaimer. Large language models are known to suffer from what researchers call "hallucinations", these being instances where the AI generates information that sounds plausible but is actually incorrect or fabricated.

The hallucination problem is particularly concerning in a search context because users may assume that information provided by Google carries the same authority as traditional search results.  When Google shows you a list of websites, you can evaluate the sources and make your own judgments about credibility.  When AI Mode provides a direct answer, that evaluation step is removed, potentially leading users to accept incorrect information as fact.

Google has implemented several measures to address accuracy concerns.  The system includes confidence scoring, so when AI Mode isn't certain about an answer, it falls back to providing traditional search results instead of generating a potentially incorrect response. There are also fact-checking systems and content filters designed to prevent the spread of misinformation.

Additionally, AI Mode typically includes citations and links to source material, allowing users to verify information if they choose to. However, as we discussed earlier, the Pew Research data suggests that very few users actually click through to verify the sources of AI-generated responses.

The environmental implications of AI Mode are also significant and often overlooked in discussions of AI capabilities. Running large language models requires enormous computational resources. Every query processed by AI Mode involves complex calculations across thousands of servers in Google's data centres.

Google has committed to sustainability goals and claims to be working on more efficient AI systems, but the environmental cost of AI Mode is likely in orders of magnitude higher than traditional search.

When we compare AI Mode to other AI systems like ChatGPT or Claude, several interesting differences emerge.  ChatGPT and similar systems are primarily conversational AI tools that generate responses based on their training data, with limited ability to access current information.  AI Mode, by contrast, combines the conversational capabilities of large language models with real-time access to Google's vast index of web content.  This gives AI Mode significant advantages in terms of current information and factual accuracy, but it also makes it more complex and potentially more prone to errors.  The system has to balance information from its training data with current web content, and these sources may sometimes conflict or provide contradictory information.

Large language models tend to reflect the biases present in their training data, which can lead to skewed or unfair responses to certain types of queries.  Google has implemented bias detection and mitigation systems, but these are ongoing challenges in AI development.

Another technical consideration is the system's handling of controversial or sensitive topics. Google has implemented content policies and safety filters, but determining what constitutes appropriate responses to complex social, political, or medical questions is inherently challenging.  The system needs to balance providing helpful information with avoiding potential harm from incorrect or inappropriate advice.

The scalability challenges are also immense. Google processes billions of search queries every day, and each AI Mode query requires significantly more computational resources than a traditional search. As adoption grows, Google will need to continuously expand its infrastructure to maintain response times and system reliability.

Looking ahead, Google is likely to continue refining and expanding AI Mode's capabilities. The company has hinted at features like more sophisticated reasoning, better integration with other Google services, and enhanced personalisation based on user history and preferences.  However, each of these enhancements brings additional technical and ethical challenges.

The success of AI Mode will ultimately depends on Google's ability to balance these competing demands, ensuring it is providing accurate, helpful responses while managing computational costs, environmental impact, and the broader implications for the information ecosystem.

The launch of AI Mode hasn't occurred in a vacuum. Across the technology industry, publishing sector, and regulatory landscape, we're seeing significant pushback and concern about the implications of Google's latest innovation.  The fact that The Independent chose to describe AI Mode as "controversial" in its headline reflects a growing scepticism about the direction of AI-powered search.

The controversy stems from several interconnected concerns that go beyond just the business disruption we discussed earlier.  At its core, the criticism centres on questions of power, control, and the future of information access in democratic societies.

This has created tension and suggestions about potential legal challenges.  Some publishers are exploring whether Google's use of their content to train AI systems and generate responses constitutes fair use or whether it represents a form of copyright infringement. These legal questions are largely untested, and the outcomes could have significant implications for the entire AI industry.

The controversy has also attracted attention from regulators and policymakers.  In the European Union, where AI Mode is notably absent, regulators have been developing comprehensive AI governance frameworks that could significantly constrain how companies like Google deploy AI systems.  The EU's AI Act, which came into effect in 2024, includes provisions that could require extensive testing, transparency, and accountability measures for AI systems that influence public access to information.

In the United States, where AI Mode first launched, there's growing bipartisan concern about the concentration of AI capabilities in the hands of a few large technology companies.  Some lawmakers have called for investigations into whether Google's AI features constitute anticompetitive behaviour, particularly given the company's dominant position in search and digital advertising.

The accuracy concerns we discussed in the technical section have also become a focal point for criticism.  While Google acknowledges that AI Mode may make mistakes, critics argue that the company hasn't done enough to address the potential for misinformation and the challenges users face in verifying AI-generated responses.

The environmental criticism has also been gaining traction.  Climate activists and environmental groups have pointed out that the massive computational requirements of AI Mode contribute to increased energy consumption and carbon emissions at a time when technology companies have committed to sustainability goals.  Some have called for greater transparency about the environmental costs of AI features and questioned whether the benefits justify the environmental impact.

Industry competitors have also weighed in, though often indirectly.  Microsoft, which has its own AI-powered search features through Bing and Copilot, has emphasised its commitment to supporting the broader web ecosystem and maintaining traffic flow to external websites. 

The academic community has been divided in its response.  Some researchers praise AI Mode as a significant advancement in information retrieval and user experience.  Others worry about the implications for information literacy, critical thinking skills, and the research process itself.  There's particular concern about how AI Mode might affect educational settings, where students may become overly reliant on AI-generated answers rather than learning to evaluate and synthesise information from multiple sources.

Interestingly, Google's own employees have reportedly expressed some concerns about the pace and scope of AI Mode's deployment.  According to reports from technology news outlets, some Google engineers and researchers have raised internal questions about accuracy, bias, and the potential for unintended consequences.  However, these internal discussions are largely confidential, and Google has maintained a unified public stance supporting AI Mode's development and deployment.

The international dimension of the controversy is also significant.  Different countries and regions have varying approaches to AI governance, data protection, and media regulation. AI Mode's phased rollout reflects, in part, the need to navigate these different regulatory environments.  The absence of AI Mode in the EU, for example, highlights how regulatory frameworks can influence technology deployment.

Some industry observers have noted that the controversy around AI Mode reflects broader tensions about the role of technology companies in society.  Google's evolution from a search engine that directed users to external websites to a platform that provides direct answers represents a shift from being an intermediary to being a destination.  This shift raises questions about market power, competition, and the responsibilities that come with controlling access to information for billions of users.

Despite the criticism, Google has maintained that AI Mode represents a positive evolution in search technology.  The company argues that users benefit from more efficient access to information and that the technology enables new types of information-seeking behaviour that weren't previously possible.  Google also points to user satisfaction metrics and engagement data as evidence that AI Mode is meeting user needs.

However, critics argue that user satisfaction in the short term may not account for longer-term implications for the information ecosystem, media diversity, and democratic discourse.  The debate reflects fundamental questions about how we balance technological innovation with broader societal values and interests.

What we're witnessing isn't just the launch of a new search feature; it's potentially the beginning of a fundamental transformation in the relationship between people and information.

The immediate future is likely to bring rapid iteration and expansion of AI Mode's capabilities.  Google has significant resources and strong incentives to improve the system's accuracy, expand its language support, and integrate it more deeply with other Google services. We can expect to see enhanced personalisation, better handling of complex queries, and possibly integration with Google's other products like Gmail, Google Docs, and Google Assistant.

But the broader implications extend far beyond Google's product roadmap.  If AI Mode proves successful and user adoption grows, we're likely to see similar features from other major technology companies.   Microsoft's Bing already incorporates AI-powered responses, and we can expect Apple, Amazon, and others to develop their own versions of AI-enhanced search and information retrieval.

This competition could drive rapid innovation, but it also raises concerns about fragmentation and inconsistency.  If different AI systems provide different answers to the same questions, users may face new challenges in determining which information to trust.  The standardisation and quality control mechanisms that have evolved around traditional web publishing may not translate directly to AI-generated content.

The economic implications are likely to unfold over several years, but the direction seems clear. Content creators, publishers, and businesses that have built their strategies around search engine optimisation and organic traffic will need to adapt to a world were AI systems increasingly mediate access to information.  This could lead to new forms of content creation specifically designed for AI consumption, new revenue models that don't depend on website traffic, and potentially new forms of partnership between content creators and AI companies.

Some publishers may choose to restrict AI systems' access to their content, either through technical measures or legal challenges.  This could create a fragmented information landscape where different AI systems have access to different sets of information, potentially leading to inconsistent or incomplete responses.

The regulatory response is likely to be significant and varied across different jurisdictions. The European Union's cautious approach, evidenced by AI Mode's absence from EU markets, may become a model for other regions concerned about the concentration of information access.  We may see new regulations specifically designed to address AI-powered search, potentially including requirements for transparency, accuracy standards, and provisions to protect the broader information ecosystem.

In the United States, the regulatory response may focus more on antitrust concerns, particularly if AI Mode significantly increases Google's market power or creates barriers for competitors. The outcome of these regulatory discussions could shape not just AI Mode's future, but the broader development of AI systems across the technology industry.

The educational implications are particularly important to consider.  As AI-powered search becomes more prevalent, educational institutions will need to adapt their approaches to information literacy and research skills.  Students who grow up with AI Mode may develop different relationships with information, potentially becoming more efficient at finding answers but less skilled at evaluating sources and understanding the research process.

There are also broader questions about how AI-mediated information access might affect critical thinking, intellectual curiosity, and the serendipitous discovery that often comes from browsing multiple sources.  If AI systems become too efficient at providing direct answers, we might lose some of the exploratory and comparative thinking that traditional research encourages.

Looking further ahead, AI Mode represents just one step toward what some researchers call "artificial general intelligence", where AI systems can match or exceed human capabilities across a wide range of tasks. The techniques and infrastructure being developed for AI Mode could eventually be applied to much more sophisticated AI assistants that can help with complex reasoning, creative tasks, and decision-making.

However, this future also brings significant risks and challenges. As AI systems become more capable and more integrated into our information infrastructure, questions about control, bias, and accountability become even more critical. The decisions made today about how to develop and deploy systems like AI Mode will have lasting implications for the future of human-AI interaction.

For individual users, the rise of AI Mode presents both opportunities and responsibilities. The technology offers unprecedented convenience and access to information, but it also requires new forms of digital literacy.  Users will need to learn how to effectively prompt AI systems, how to verify AI-generated information, and how to maintain critical thinking skills in an environment where answers are increasingly provided rather than discovered.

The success or failure of AI Mode will ultimately depend on how well Google and other companies can balance the competing demands of innovation, accuracy, economic sustainability, and social responsibility.  The technology has the potential to democratise access to information and make knowledge more accessible to people around the world.  But it also has the potential to concentrate power, reduce information diversity, and create new forms of digital inequality.

It's clear that we're at a pivotal moment in the evolution of information technology.  The decisions made by companies, regulators, and users over the next few years will shape how we access and interact with information for decades to come.

Whether AI Mode represents a positive evolution or a concerning concentration of power may depend on how successfully we can address the challenges I've discussed today,  maintaining accuracy and reliability, preserving economic sustainability for content creators, ensuring regulatory oversight, and protecting the diversity and quality of information that makes the web valuable.

For now, AI Mode remains an optional feature, and users can choose whether to embrace this new way of searching or stick with traditional methods.  But as the technology improves and becomes more integrated into our digital infrastructure, that choice may become less meaningful.

The story of AI Mode is still being written, and all of us have a role in shaping how it unfolds.  The key is to remain informed and engaged as we navigate this new landscape of AI-mediated information access.  As this technology continues to evolve, I'll be watching closely and bringing you the analysis you need to understand its implications for our digital future.

Well, that is all for today. Thanks for tuning in to Inspiring Tech Leaders. If you enjoyed this episode, don’t forget to subscribe (it actually does help me), leave a review, and share it with your network.  You can find more insights, show notes, and resources at www.inspiringtechleaders.com

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