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Today, we’re bringing you the latest in AI-powered marketing and business strategies. Here’s what’s inside:
🚨 AI Top Story: Microsoft says AI “business agents” could replace today’s SaaS apps by 2030. Reshaping how teams work and how companies spend on software.
🔧 AI Tool Of The Week: Meet Conversion. the AI-native platform that replaces clunky rule-based marketing automations with workflows that learn and adapt in real time.
🌟 Creator Spotlight: Jonathan Parson shares how to use GPT 5 to run a full competitor analysis in just 30 minutes.
💬 AI Use Case Of The Week: Heineken tapped AI to analyse millions of social conversations and sales signals to spot emerging flavour trends - leading to the launch of Heineken Silver, now one of their fastest-growing products worldwide.
🎥 YouTube Resource Of The Week: 8 game-changing ChatGPT agent use cases that cut hours off your workflow
Will SaaS Still Exist in 2030?
Microsoft Sees AI Agents Taking Over by 2030
Every business today runs on a stack of SaaS apps. Sales teams live in the CRM, finance keeps things running in ERP, marketing leans on a mix of tools from analytics to content platforms, and operations ties it all together with dashboards and other systems.
It’s the setup most companies rely on. But according to Charles Lamanna, Microsoft’s Corporate VP of Business Applications and Platforms, the way we interact with software is going to look very different in just a few years. By 2030, he says, AI “business agents” won’t just support these apps, but they’ll replace them.
His reasoning comes down to adaptability. Traditional apps are built to do one job. Agents can adjust to the task at hand, pulling information from across systems and returning a complete outcome. Instead of moving between tools to create a quarterly sales report, you’d describe what you want and the agent would deliver it.
If that vision plays out, the software landscape looks very different. Companies may no longer spread budgets across dozens of SaaS licenses. Spending could shift toward a single platform of agents that handle multiple needs. Buying decisions would focus less on features inside an app and more on the strength of an ecosystem.
For marketers, this shift could touch almost every part of the job. An agent could analyse performance data, but it could also pull audience insights, suggest creative directions, generate content variations, and even adjust personalisation rules in real time. Instead of working across a patchwork of analytics dashboards, campaign tools, and content platforms, marketers could collaborate with a single agent that moves fluidly from strategy to execution.
Microsoft has already reshaped its teams to make agents central to the strategy. Our familiar dashboards and SaaS tools won’t vanish overnight, but the way we engage with them could look totally different by 2030.
🤝 OpenAI Updates GPT-5 for a Warmer, More Approachable Interaction Experience- OpenAI on X - After GPT-5’s launch, user feedback pushed OpenAI to dial back its formality - adding warmer, more natural touches to make interactions feel less stiff.
💸 Cutting AI Costs: Smart Strategies for Small Business Savings - Dynamic startups are slashing AI inference costs to make powerful tools affordable for freelancers and small companies, helping dismantle barriers to advanced AI use.
📈 AI start-up Cohere raises $500mn as it challenges OpenAI for business clients - Cohere just raised $500 million at a $6.8 billion valuation, doubling its revenue to $100 million and positioning itself as an enterprise‑ready rival to OpenAI with a focus on security and compliance.
🏗️ Building an AI-first company: What these two business leaders learned from top experts - Co‑authors Adam Brotman and Andy Sack unpack insights from conversations with leaders like Sam Altman and Bill Gates
🚀 Elon Musk says Google has the best shot at being the leader in AI - Elon Musk conceded that Google currently leads the AI race thanks to its unmatched compute and data muscle.
🎯 The Artificially Intelligent Enterprise - Superintelligence
💡 AI CIO - The Hidden Risk in AI-Created Code
☕ AI Tangle - Perplexity's $34.5B Chrome Bid, Sam Altman's Neuralink Rival & An xAI Co-Founder's Exit
📻 AI Confidential Podcast - Agents Are the New API Client with Marco Palladino
Bring Adaptive Intelligence to Your Marketing With Conversion
If you’ve ever wished your marketing automation could think a step ahead, Conversion is must-try AI tool. Backed by $28 million in new funding, it’s an AI-native platform built to replace rule-based automations with intelligent, adaptive workflows.
Instead of setting up endless “if this, then that” rules, Conversion learns from campaign performance in real time. Launch an email, and it can automatically adjust send times based on open behaviour. Run ads, and it can rebalance budget mid-flight when one channel starts outperforming another. It doesn’t just execute the rules you give it—it recommends and acts on smarter ones.
That makes it especially appealing for teams juggling multichannel campaigns. A marketer could centralize their paid, email, and social workflows inside Conversion, then let the AI spot underperforming segments, tweak creative, and shift spend—all without building dozens of separate automations or pulling constant manual reports.
Why It’s Gaining Traction
Marketers are paying attention because Conversion isn’t just retrofitting AI into a legacy tool. It was designed around AI from day one.
With fresh funding and fast growth, it’s being seen as a leaner, more adaptive alternative to heavyweight enterprise platforms that require armies of admins to set up. Early adopters say the biggest benefit is speed: campaigns launch quicker, and optimizations happen continuously rather than in reporting cycles.
Key AI Features
Self-Optimising Workflows: Learns from results and updates automation rules on its own.
Budget Intelligence: Reallocates spend dynamically across channels.
Cross-Channel Coordination: Runs email, ads, and social together with one brain.
Creative Guidance: Surfaces AI-backed suggestions when performance dips.
Real-Time Adaptation: Monitors campaigns live and makes changes instantly
JONATHAN PARSONS - A step-by-step AI workflow to run competitor analysis in just 30 minutes.
Heineken Uses AI to Brew Up a Hit Product 🍺
Heineken tapped AI to analyse millions of social conversations and sales signals to spot emerging flavour trends. The insights pointed to a growing demand for a lighter, smoother lager - leading to the launch of Heineken Silver, which has since become one of the brand’s fastest-growing products worldwide.
How It Worked
Listening at scale
AI models scanned social chatter, reviews, and cultural signals to identify what consumers wanted in their next beer — from taste preferences to lifestyle cues.
Connecting sales and sentiment
By linking social insights with retail sales data, Heineken validated whether online hype matched real-world buying behavior.
Turning insights into innovation
The AI-driven analysis gave product teams a clear direction: launch a premium, lighter lager to capture younger drinkers and health-conscious consumers.
Replicate Something Similar
Step 1: Use AI for Trend Detection
What it does: Scans social platforms, forums, and reviews for early signs of emerging consumer preferences.
Tools: Brandwatch.
Step 2: Validate With Sales Signals
What it does: Cross-checks social buzz against retail or e-commerce sales to separate hype from substance.
Tools: Snowflake + Dataiku, NielsenIQ, RetailNext.
Step 3: Feed Insights Into R&D or Campaigns
What it does: Translates consumer signals into product tweaks, packaging updates, or new launches.
Tools: Ailytic, Crayon, or even in-house dashboards built on Looker/Power BI with AI integration.
8 game-changing ChatGPT agent use cases that cut hours off your workflow
See exactly how these agents handle real business tasks from start to finish
GPT-4 was obviously way more than an LLM to ya’ll…🥺
