Category Artificial Intelligence and Machine Learning

What Google and Microsoft patents teach us about GEO

By in Artificial Intelligence and Machine Learning

Written by Olaf Kopp Search patents reveal how AI search systems interpret intent, evaluate content passages, and build brand understanding in generative results. Generative engine optimization (GEO) represents a shift from optimizing for keyword-based ranking systems to optimizing for how generative search engines interpret and assemble information.  While the inner workings of generative AI are famously complex, patents and research papers filed by major tech companies such as Google and Microsoft provide concrete insight into the technical mechanisms underlying generative search. By analyzing these primary sources, we can move beyond speculation and into strategic action. This article analyzes the most insightful patents…

Read More

How AI-Driven Creative Is Redefining B2B Advertising Performance

By in Artificial Intelligence and Machine Learning, Marketing

by James Wilson B2B advertising has finally outgrown its obsession with vanity metrics. Today, the smartest players in advertising are trading broad impressions for tangible business outcomes. Traditional metrics such as click-through rates and eCPM are increasingly insufficient for enterprises that demand demonstrable contributions to revenue, pipeline acceleration, and long-term customer value. Concurrently, the rapid evolution of AI—particularly generative and predictive models—is enabling marketers to reimagine creative development, audience engagement, and performance optimization with a results-centric lens. AI-driven creative approaches are transforming B2B advertising performance, moving teams from insight generation to tangible impact. The Traditional Paradigm: Why Change Was Necessary Historically,…

Read More

Inspiring examples of responsible and realistic vibe coding for SEO

By in Artificial Intelligence and Machine Learning Tag

Written by Gus Pelogia Learn vibe coding: Use AI tools to build apps without coding. This guide covers setup, limits, risks, and SEO tool examples to inspire your own projects. Vibe coding is a new way to create software using AI tools such as ChatGPT, Cursor, Replit, and Gemini. It works by describing to the tool what you want in plain language and receiving written code in return. You can then simply paste the code into an environment (such as Google Colab), run it, and test the results, all without ever actually programming a single line of code. Collins Dictionary named…

Read More

Seven Ways To Sharpen Sales Coaching with AI

By in Artificial Intelligence and Machine Learning, Sales, Training

BY GEORGE BRONTÉN Even with all the technology that has rolled out in the past few years, coaching is still the critical multiplier in complex sales. It’s still the hinge point on which your sales team grows or stagnates. And the good news is: AI can help your coaches do a better job of it. Let’s look at how. 7 Ways to Use AI in Your Coaching Sales coaches who leverage AI today will easily outperform coaches who avoid it. As in so many other things, effective AI use can be a power multiplier. For coaching, you can use it to: Summarize past coaching…

Read More

The Role of Websites in the Age of AI

By in Artificial Intelligence and Machine Learning, Marketing

by Shawn Davis Websites have been the cornerstones of the internet economy for years. In the new age of AI, however, many are questioning if this still rings true. With organic traffic decreasing by up to 64 percent, a new AI browser launching every day, and consumers increasingly handling their needs through AI chat interfaces, brands are looking at their online presences through fresh eyes. Consumers have fewer reasons to leave their favorite LLMs to browse, research, and even purchase new products. This is upending the way we use the internet, and website builders are asking themselves what role, if any, webpages…

Read More

Why SEO teams need to ask ‘should we use AI?’ not just ‘can we?’

By in Artificial Intelligence and Machine Learning Tag

Written by Claire Taylor Automation can save SEO teams time—but at what cost? Explore where AI boosts speed, where it erodes trust, and how to protect real authority. Right now, it’s hard to find a marketing conversation that doesn’t include two letters: AI. SEOs, strategists, and marketing leaders everywhere are asking the same question in different ways: How do we use AI to cut manpower, streamline work, move faster, and boost efficiency? Much of that thinking makes sense. If you run a business, you can’t ignore a tool that turns hours of grunt work into minutes. You’d be foolish to try.…

Read More

Redefining procurement performance in the era of agentic AI

By in Artificial Intelligence and Machine Learning

By Aasheesh Mittal, Roman Belotserkovskiy, and Theano Liakopoulou Agentic AI is changing what the procurement function can achieve—shifting procurement’s focus from transaction tasks to a strategic driver of growth, sustainability, and resilience. https://w.soundcloud.com/player/?url=https%3A//api.soundcloud.com/tracks/2260728350&color=%2307254d&inverse=false&auto_play=false&show_user=true Procurement is entering a new age—one defined not just by cost containment, but by its ability to shape broader enterprise outcomes: resilience, sustainability, speed to market, and innovation. Yet today’s procurement teams are struggling to keep pace. Rapid shifts in the geopolitical environment, market dynamics, supply shocks, inflationary pressure, and an overwhelming volume of data are all converging to expose the limits of traditional operating models. Procurement leaders tell us…

Read More

7 real-world AI failures that show why adoption keeps going wrong

By in Artificial Intelligence and Machine Learning

Written by Bruce Clay From illegal trades to chatbot lawsuits, these examples reveal the operational, legal, and reputational risks behind failed AI deployments. AI has quickly risen to the top of the corporate agenda. Despite this, 95% of businesses struggle with adoption, MIT research found. Those failures are no longer hypothetical. They are already playing out in real time, across industries, and often in public.  For companies exploring AI adoption, these examples highlight what not to do and why AI initiatives fail when systems are deployed without sufficient oversight. 1. Chatbot participates in insider trading, then lies about it In an experiment driven by the…

Read More

Top 10 AI Marketing Tools for Small Businesses in 2026

By in Artificial Intelligence and Machine Learning, Marketing

By Lauren Basiura Everyone knows it at this point, but AI is a big deal in modern marketing. Small businesses can now access tools that used to be limited to large enterprises. These platforms automate repetitive tasks, improve targeting, and help create more effective campaigns with fewer resources. Understanding which tools are worth the investment helps small teams compete more effectively. The right AI tools can manage social media, generate ad copy, optimize SEO, and analyze customer data – all while saving time and improving accuracy. Quick Takeaways AI tools help small businesses automate daily marketing tasks. Personalization and predictive…

Read More

Real AI CRM use cases driving revenue growth in 2025

By in Artificial Intelligence and Machine Learning, Revenue

Written by: Diego Mangabeira Artificial intelligence has shifted from a helpful add-on in CRM systems to a core capability. AI-powered systems analyze behavior, predict intent, automate follow-ups, and personalize experiences at scale. As a result, AI CRM use cases are quickly becoming essential for revenue teams that want to move faster and deliver a more consistent customer journey. Learn more about why HubSpot's CRM platform has all the tools you need to grow better. Companies adopting AI-native CRMs are already seeing meaningful improvements in their sales processes. In fact, teams using HubSpot AI sales features see a 48% decrease in average time to close. Beyond…

Read More