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<h3>TLDR: Google’s AgentSpace marks a shift from demos to deployable agents. These aren’t chatbots, they’re autonomous units that run workflows, escalate tasks, and interact with tools across the tech stack. This blog explains how enterprise teams can prepare for agent based collaboration, without waiting for IT to catch up.</h3><h2>What Is Google AgentSpace?</h2>AgentSpace isn’t just another AI feature release. It formalises what many teams have been hacking together with custom GPTs, Make.com, and internal tools.What Google now offers natively:<ul><li>Agent infrastructure with memory, logic, and multi-step task handling </li><li>Integrations across Workspace, Vertex AI, and third-party APIs </li><li>Agent lifecycle tools (permissions, identity, context retention) </li><li>A UI for building and managing them inside enterprise environments </li></ul>In short, agents are now products, not just prompts.<h2>From Tool Users to Agent Designers</h2>Most teams aren’t set up to handle this currently. They think in terms of tools and dashboards because that is how it has always been, but not in terms of autonomous agents that behave like junior staff.That requires a new layer of thinking:<ul><li>What role does the agent play in your workflow? </li><li>What decisions should it make alone vs escalate? </li><li>How does it coordinate with people, not just tools?</li></ul><h2>Real Example: Workflow Agents in Action</h2> A national logistics firm tested agent-based tracking and alerts across their operations.Before:<ul><li>Manual data entry across 4 systems </li><li>Alerts via Slack when someone remembered </li><li>Escalations missed on weekends </li></ul>With agents:<ul><li>AI monitors order flow and stock levels in real time </li><li>Flags anomalies and escalates before they breach SLA </li><li>Operates 24/7 with audit logs and explainable actions</li></ul>This saved 30+ hours per week and reduced missed handovers by 80%.<h2>Getting Ready for AI Agents</h2>The tech now exists. But your processes, roles, and governance really don’t.So this is how you should prepare:<ol><li>Map your workflows: Where can an agent act without human delay? </li><li>Redesign roles: Create space for agents to perform, not just assist </li><li>Define escalation rules: Make clear when human review is needed </li><li>Prototype in no-code: Use tools like Make, Airtable, or AgentSpace itself to test live flows</li></ol>What This Means for Team Collaboration In a post-AgentSpace world:<ul><li>Meetings drop, handoffs shrink, and tool fatigue lessens </li><li>Success depends on how well the agents are briefed </li><li>Collaboration becomes a system design challenge</li></ul>That’s why our <a data-mce-href="https://aistrategyconsulting.com.au/introduction-to-ai-5-day-bootcamp" href="https://aistrategyconsulting.com.au/introduction-to-ai-5-day-bootcamp">AI Bootcamp </a>focuses on agent orchestration and workflow redesign, not just prompts and tools. We help you prototype, pilot, and govern agents in a way your team can actually use.<h2>&nbsp;FAQ</h2>Q: How is AgentSpace different from using ChatGPT or Gemini? A: ChatGPT is a conversation tool. AgentSpace builds long-running, autonomous agents with memory, logic, and tool access. It’s a platform, not a chatbot.Q: Do I need developers to use this? A: No. You can build agents with no-code tools or via UI-based templates. Technical teams help scale, but non-technical teams can start now.Q: What’s the risk of deploying agents too early? A: Poorly scoped agents can flood teams with noise or make silent mistakes. Start small, use audit logs, and apply clear rules on what’s agent-led vs human-controlled.&nbsp;Don’t wait for an AI Centre of Excellence to approve a year-long pilot. Start by redesigning just one workflow and watch the handoffs disappear.&nbsp;Join the <a data-mce-href="https://aistrategyconsulting.com.au/introduction-to-ai-5-day-bootcamp" href="https://aistrategyconsulting.com.au/introduction-to-ai-5-day-bootcamp">AI Bootcamp </a>or book a Readiness Assessment to build your first agent-ready process.

What Google's "AgentSpace" Means for Workflows

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TLDR: Agentic AI doesn’t just process data, it chooses what to research, how to analyse it, and when to stop. That shift rewires the role of researchers from knowledge workers to system architects. This post explains what agentic AI means for research teams, and how to prepare using no-code tools and workflow redesign.<h2>Why Research Teams Can’t Ignore Agentic AI</h2>Traditional research relied on human-driven questions, manual methods, and linear reporting. Then came LLMs, which helped summarise results or automate small parts of analysis.&nbsp; Agentic AI goes further.It doesn’t wait for instructions. It defines the problem, fetches data, tests ideas, and refines results—all without a human in the loop at every step. For research leaders, this means your team’s value isn’t doing the work. It’s designing how the work gets done.<h2>What’s Different About Agentic AI in Research?</h2><ul><li>It decides what’s relevant: Agentic agents aren’t just retrieval bots. They weigh sources, reject irrelevant material, and pivot their search in real-time. </li><li>It iterates autonomously: You give it a goal (e.g. "Find emerging risks in climate finance"), and it cycles through plans, tests prompts, filters noise, and narrows in on insights. </li><li>It stops itself: Based on thresholds you set, it knows when to finish. No more over-researching or half-done threads.</li></ul>This moves research from a task-based job to a system-level challenge.<h2>What Should Research Leaders Do Now?</h2>If your team writes 40-page reports or spends weeks on literature reviews, that structure needs rethinking.Instead:<ul><li>Redesign workflows around agents, not people </li><li>Focus on quality thresholds, risk settings, and escalation triggers </li><li>Use no-code tools to prototype agent workflows without relying on dev teams </li></ul>Don’t wait until a competitor publishes in half the time with better source coverage.<h2>Example: Agentic Research in Action</h2>A policy advisory firm built an agentic research assistant to monitor regulatory updates across Southeast Asia.The old method:<ol><li>4 researchers </li><li>Manual checks of 25 sites </li><li>3-day lag for compilation </li></ol>The new setup:<ol><li>An agent triggers daily scans </li><li>Uses LLMs to translate, tag, and flag high-risk changes </li><li>Escalates only what matters to a human reviewer</li></ol>It cut workload by 60%, reduced turnaround to 6 hours, and improved accuracy.<h2>The Real Shift: From Analysts to System Architects</h2>Research professionals won’t disappear but their skillset will change.You’ll need:<ul><li>A grip on AI agents and how to prompt them </li><li>The ability to structure a research question for machine execution </li><li>Skills to build guardrails and validate outputs </li></ul>That’s what you learn in our <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">AI Fundamentals Masterclass</a> and develop in the <a data-mce-href="https://aistrategyconsulting.com.au/introduction-to-ai-5-day-bootcamp" href="https://aistrategyconsulting.com.au/introduction-to-ai-5-day-bootcamp">AI Bootcamp</a>. We teach non-technical teams to turn workflows into agent-ready systems.<h2>&nbsp;FAQ</h2>Q: Is agentic AI safe to use for critical research? A: Yes, but only with strong guardrails. Define scope, escalation points, and review logic to ensure responsible use.Q: Do I need a data science team to use this? A: No. Many agentic tools are no-code or low-code. Most of our clients use Airtable, Make, or Claude with structured prompt flows.Q: What’s the first step to redesigning our research process? A: Start with a Readiness Assessment. We’ll map your existing workflow and show you where agents can save time or improve quality.Ready to start? Run your Readiness Assessment or join the next <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">Masterclass.</a> &nbsp;

How Agentic AI Is Rewriting the Rules of Market Research

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<h3>TLDR: AI isn’t just for writing copy—it can now help you run entire market research sprints in hours, not weeks. Use it to spot trends, extract customer pain points, and turn raw data into testable campaigns. You don’t need a data scientist. You need a clear process, the right tools, and a few good prompts.</h3><h2>Why AI matters for market research now</h2>Most market research is too slow to be useful.By the time the report lands in your inbox, the trend has moved on, the campaign’s out, and your competitor’s already testing new angles.AI changes that. You can now use off-the-shelf tools to:<ul><li>Pull live customer sentiment from reviews or Reddit threads </li><li>Group feedback into themes by behaviour or need </li><li>Predict what features matter most next quarter </li><li>Draft campaigns directly from those insights</li></ul><h2>The real reason teams get stuck</h2>Most non-technical teams don’t lack ideas, they lack a process.They hear “AI can help with research,” but then what?They don’t know:<ul><li>What tools to use </li><li>What questions to ask </li><li>How to prompt AI correctly </li><li>What to do with the results </li></ul>So they revert to guesswork or overpay for old-school reports. Here’s how to break that pattern.<h2>What to actually do: a 5-step AI market research loop</h2><ol><li>Pick a real question Not “what do customers want?” Try: “Which product features get mentioned most in 3-star reviews?” “What objections come up in competitor ads or comment threads?” </li><li>Find raw material Copy Reddit threads, app store reviews, support chat logs, or survey responses.</li><li>Paste it all into ChatGPT. Extract themes Use prompts like: “List the top 3 problems mentioned.” “Group responses by pain point or motivation.” “What patterns repeat across this feedback?”</li><li>Ask for predictions “Based on this, what feature or need is most likely to influence conversion in the next 3 months?” </li><li>Draft a test “Write a headline and subheading for an email campaign focused on the top pain point.” Then run it. Learn. Repeat.That’s how you close the loop: insight → message → market.</li></ol><h2>Tools that actually work for this</h2>You don’t need custom models. Start with:<ul><li>ChatGPT: For extraction, pattern-finding, and drafting </li><li>Perplexity: For live web answers (skip Google rabbit holes) </li><li>Fireflies/Otter: Transcribe interviews or sales calls </li><li>Notion AI or Mem: For tagging notes and turning them into themes </li><li>Google Sheets + AI plugins: For clustering and prioritising ideas </li></ul>Use what you already have. These fit into workflows, not around them.<h2>Why this works for marketing, product, and sales</h2>You’re not “doing AI.” You’re researching faster and getting better answers.<ul><li>Marketing stops guessing what language to use </li><li>Product stops building based on internal opinions </li><li>Sales gets fresher, sharper objection-handling language </li></ul>And your team learns how to use AI the right way.<h2>Want to teach your team how to do this properly?</h2>We teach teams how to use AI for real research—without needing technical skills or buying expensive tools.The <a data-mce-href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass" href="https://aistrategyconsulting.com.au/ai-fundamentals-masterclass">AI Fundamentals Masterclas</a>s gives you the why and how. The 5-Day AI Bootcamp walks you through it live:<ul><li>Your data </li><li>Your customer language </li><li>Your questions </li><li>Your outputs</li></ul>So your team walks away with workflows they can actually reuse.<h2>FAQs</h2>Q: Do I need AI experience to do this? A: No. If you can use ChatGPT and Google Docs, you can run this process.Q: Is this just for marketing? A: No. Product, support, and sales teams all benefit from fresh insight and clearer messaging.A: How do I avoid bad data or false trends? A: Use real, recent inputs. Validate AI outputs with your team. Don’t let the model think for you—make it think with you.A: What’s the best place to start? A: Start with a real customer question you don’t know the answer to. Then run the five steps above. Or bring us in, and we’ll guide your team through it.

How AI Can Speed Up Market Research for Non Techie Teams

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<h3>TLDR: Generative AI tools aren’t magic—they’re data, algorithms, and compute power working together. But their impact on content creation and business storytelling is profound. If you treat language as a system—whether it’s customer queries, video scripts, or internal comms—AI can help you produce better stories, faster, and at scale.</h3><h2>Why storytelling still matters in the age of AI</h2>Storytelling isn’t dead. It's just changed form.In the past, companies told stories in brochures, scripts, or brand videos. That still happens, but now, story flows through your support chatbot, explainer pages, onboarding emails, product UI, and even code documentation.Every part of your business “speaks.” And AI helps you write all of it without needing a writer in every room.That’s why businesses are rethinking content as a system of language: every interface, every function, every touchpoint. According to IBM’s Darío Gil, “If you squint, everything starts to look like a language that can be deciphered and understood.” And once it’s language, it’s trainable.This isn’t just about automating copy. It’s about building community, clarity, and trust.<h2>What is generative AI, really?</h2>Strip the hype. At its core, generative AI is just a way of predicting what comes next based on patterns in huge volumes of data.<ul><li>Early deep learning used labelled data with humans tagging content </li><li>Then came transformers and self-supervised learning </li><li>Now we have foundation models that&nbsp; adapt to your domain, tone, and data </li><li>These models don’t “know” things. They simulate knowledge by predicting words, images, or audio sequences with high probability.</li></ul>What that means for your business: You can use generative AI to rapidly generate original content—but only if your inputs are strong, your domain is clear, and your purpose is well-scoped.The model is only as good as what you feed it and how you guide it.<h2>How content creation is being reshaped </h2>Most enterprise content teams don’t need a poet. They need a system.AI changes how we scale content creation by:<ul><li>Turning past documentation into training data for new comms </li><li>Rewriting tone for different channels or audience segments </li><li>Autocompleting templates, reports, onboarding guides, or internal wikis </li><li>Synthesising video transcripts or meeting notes into usable formats </li></ul>More importantly, AI enables community co-creation. If your audience is engaged, so think forums, comment threads, social channels then you can train on that data, amplify their voice, and produce content with them, not just for them.<h2>Tools You Should Be Using</h2><ul><li>ChatGPT / Claude / Gemini: For quick script generation, tone rewriting, or internal wiki drafting. </li><li>Descript or OpusClip: Turn video recordings into text and summarise them for distribution. </li><li>Mem / Notion AI / Scribe: Build living documentation or training guides from scattered inputs. </li><li>ElevenLabs / Murf / Runway: Convert text to synthetic voiceovers or visual B-roll for presentations or short-form video. </li></ul>Start with one channel: say, your onboarding emails. Use AI to:<ol><li>Transcribe and summarise your team walkthrough videos. </li><li>Draft a three-part welcome sequence in your voice. </li><li>Personalise versions based on job role or segment.</li></ol><blockquote>Your job shifts from writing everything manually to curating structure, tone, and intent.</blockquote><h2>Protect your data. It's your content edge.</h2>Gil’s final warning lands clearly: don’t outsource your data.If your AI storytelling system relies on someone else’s data or model, you’re handing over your differentiation. The businesses doing this well are:<ol><li>Treating internal comms, chat logs, customer feedback as gold </li><li>Fine-tuning models on that trusted data </li><li>Layering their tone, vocabulary, and IP on top </li></ol>Here’s a simple AI-powered framework for small teams:Your AI-Powered Content System&nbsp; <ul><li>Collect your raw material Pull transcripts, meeting notes, support chats, or internal docs using tools like </li><li>Otter or Fireflies. Summarise into usable outlines </li><li>Use ChatGPT or Claude to extract key points, themes, or bullet summaries from messy source material. </li><li>Draft your content Turn those summaries into first-draft articles, emails, scripts, or social posts with </li><li>ChatGPT, Gemini, or Claude. Adapt for each format or channel </li><li>Tweak tone, voice, and structure for different audiences or platforms using Jasper, Copy.ai, or Notion AI. </li><li>Publish and distribute efficiently Use tools like Notion, Airtable, or Zapier to build a lightweight workflow that gets the right content to the right peoplewithout endless back-and-forth.</li></ul><h2>Start building your AI content capability</h2>Don’t wait for a Chief AI Story Officer. You already have the pieces:<ul><li>SMEs who understand your product </li><li>Ops teams buried in documentation </li><li>Brand people who care about voice </li></ul>Start with a small project: automate internal FAQs. Build a chatbot on your support docs. Use AI to rewrite your tone guide for five new formats.That’s how you build capacity, credibility, and content that speaks like your business not a tech demo.Want to scale your content creation and community impact—without losing your voice? &nbsp;Start by building foundational AI fluency across your team. Our AI Fundamentals Masterclass is designed for non-technical teams ready to experiment, build, and ship value.<h2>FAQs</h2>Q: What kind of content can generative AI create? A: Text, images, audio, video. If it can be represented in data, it can be generated—provided your inputs and guardrails are strong.Q: Isn’t AI content generic? A: Only if your data is. When you fine-tune models on your brand voice, customer data, and domain-specific knowledge, the results reflect your identity.Q: How does AI help with community building? A: AI can surface patterns in user feedback, personalise responses, and even generate content alongside users—turning passive audiences into co-creators.Q: Do I need my own model? A: No. But you need to control how the model is used—your prompts, your data, your oversight.

How to Use Gen AI For Storytelling and Content Creation

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<h3>TLDR: Canvas is a visual builder inside ChatGPT. It lets you create simple, functional AI tools without code. You can design forms, outputs, and layouts that match how your team already works. If you run a service business, this means less switching between apps, fewer manual tasks, and faster delivery. We help teams use Canvas to replace spreadsheets, simplify client workflows, and systemise what already works.</h3><h2>The Real Problem With AI Adoption&nbsp;</h2>For most teams, the issue isn’t access to AI. It’s integration.They’re told to “use ChatGPT,” but it sits outside their workflow. It’s another tab. Another thing to prompt. Another tool that doesn’t talk to anything else.&nbsp;That’s why it gets abandoned. Not because it’s bad, but because it’s disconnected.&nbsp;Canvas solves this by letting you design the tool around your process.<h2>What Is ChatGPT Canvas?</h2>Canvas is a new feature inside ChatGPT. It’s a visual interface builder—you drag in blocks, add inputs, shape outputs, and control how your AI tool looks and functions.What’s different:<ul><li>You don’t need to prompt every time. You create a reusable interface. </li><li>You can guide users step-by-step with structured forms, dropdowns, or tabs. </li><li>You can set it up to return outputs in tables, PDFs, summaries, or instructions. </li></ul>Think of it as building your own AI-powered app without writing a single line of code.<h2>How Service Teams Are Already Using Canvas</h2>We’ve helped clients build lightweight internal tools using Canvas to cut time, cost, and back-and-forth.1. Client Brief Parser Instead of manually extracting scope from intake forms, this tool:<ul><li>Accepts form data or meeting notes </li><li>Summarises the project type, complexity, and flags </li><li>Drafts a project brief, ready for approval </li></ul>2. Review Assistant Used in an HR team to review CVs and generate interview scorecards:<ul><li>Upload candidate info </li><li>Match to job criteria </li><li>Generate behavioural questions and score templates </li></ul>3. Content Planning Workspace For a marketing consultancy juggling 12 brands:<ul><li>Inputs: campaign type, tone, goals </li><li>Outputs: content angles, suggested formats, 7-day content calendar </li><li>Bonus: connects to Airtable to track status </li></ul>Each one was built in under 2 hours. And each one now saves hours weekly.<h2>Why This Matters If You’re Not Technical </h2>Most SMEs aren’t short on ideas—they’re short on time.They don’t need another AI tool. They need the right wrapper around the one they already have.Canvas gives you that:<ol><li>You design the flow, not just the response</li><li>You create the tool, not just a prompt </li><li>You shape it once and reuse it across the business </li></ol>And the best part? Anyone can do it with the right support on what to build and how.We can help you:<ul><li>Identify the 1–2 processes causing friction (proposal writing, onboarding, planning) </li><li>Map what inputs and outputs you need </li><li>Build a Canvas that guides your team step-by-step </li><li>Test and improve it with real work, not just a demo </li></ul>One client replaced a 14-step onboarding doc with a single Canvas. Their VA now uses it to run intake calls with zero supervision.&nbsp;Don’t Prompt Harder. Build Smarter.The gap isn’t in the AI. It’s in the setup. Canvas is now available to everyone. But knowing what to build, and how to make it useful, and that’s where the value lies.&nbsp;We don’t teach theory. We build practical, <a data-mce-href="https://aistrategyconsulting.com.au/ai-no-code-low-code-implementation" href="https://aistrategyconsulting.com.au/ai-no-code-low-code-implementation">low code AI tools</a> with your team that reflect how you work.<h2>FAQs</h2>Q: Do I need to know how to code to use Canvas? No. If you can use a form builder like Typeform or Notion, you can use Canvas. It’s drag-and-drop.Q: Will this replace my current software? It can. Many clients have replaced Airtable setups, Google Sheet calculators, or PDF templates with one Canvas.Q: Can my whole team use the same tool? Yes. Once built, you can share the link or embed the tool in your internal systems.Q: What if I don’t know what to build first? We help you choose a starting point based on where time is lost or processes break down.

How to Use ChatGPT Canvas to Simplify Your Work

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<h3>TLDR: ChatGPT now supports real-time screen sharing and live video analysis. That means you can use AI to watch your workflows, interpret documents on-screen, and respond like a human would. If you run a service business, this shifts AI from a passive assistant to a hands-on operator—able to do tasks across tabs, calls, and content. And we show clients exactly how to use it.</h3><h2>&nbsp; What Just Happened: ChatGPT Went Multimodal (And What That Means)</h2>Until now, most AI tools have relied on text prompts. You ask a question, get an answer. Basic, useful, but limited.That’s changed. OpenAI just gave ChatGPT the ability to work multimodally—meaning it can take in different types of input at once: screen activity, live video, images, and voice. It doesn’t just read text. It sees, listens, and interprets what’s happening right now.This is a leap. Not because it looks cool in a demo. Because it unlocks entirely new use cases inside your business.<h2>&nbsp; What This Means for Real Work</h2>Here’s what most service teams juggle daily:<ul><li>Switching between tabs to pull info from five tools </li><li>Explaining what’s on screen during remote support or training </li><li>Reviewing visual documents (dashboards, scanned PDFs, charts) </li><li>Sharing context on-the-fly in client meetings </li></ul>Now imagine ChatGPT sitting beside you, watching your screen, and helping in real time:<ul><li>Spotting errors in a spreadsheet you’re scrolling through </li><li>Suggesting next steps based on what’s on your screen </li><li>Summarising what’s happening in a Zoom call </li><li>Interpreting a chart or policy PDF you’re showing</li></ul>This isn’t some future fantasy. It’s already rolling out.<h2>From Assistant to Operator: Why This Change Matters</h2>Before this update, ChatGPT was reactive. It could only respond to what you typed. Now it can initiate action based on what it sees and hears.For example:<ul><li>You're reviewing contracts on a video call. ChatGPT can extract risks, flag inconsistent clauses, and suggest edits as you scroll. </li><li>You’re training a new hire. It can observe the workflow and document SOPs automatically based on what you do on screen. </li><li>You’re troubleshooting a process. ChatGPT can interpret dashboards, spot anomalies, and recommend fixes—in real time. </li><li>That’s not an assistant. That’s a junior team member who works across formats and context.</li></ul><h2>Why Most Businesses Will Still Miss the Opportunity</h2>Because the tech isn't the hard part. It’s knowing how to frame the task, what to show it, when to prompt it, and where to hand things over to a human.That’s what we do at <a data-mce-href="https://aistrategyconsulting.com.au/" href="https://aistrategyconsulting.com.au/">AI Strategy Consulting</a>:<ul><li>We show you where multimodal AI saves time </li><li>We design workflows around your real service work </li><li>We help your team adopt it without panic or jargon </li><li>We don’t sell the tool. We make sure it actually works for you.</li></ul><h2>Real Example: Policy Review on Screen</h2>One of our clients handles policy documents for aged care compliance. They used to manually copy policy text into ChatGPT to get summaries or risk notes. Now, with screen share active, ChatGPT:<ul><li>Watches them scroll the document </li><li>Flags critical clauses </li><li>Auto-generates notes based on the screen content </li><li>Suggests missing compliance language in real time </li></ul>No text pasted. No reformatting. Just faster output in the moment the work is happening.&nbsp;They didn’t need to switch apps or redo the process. They just turned on a new mode.<h2>The Small Shift That Changes Output</h2>Multimodal tools don’t mean you throw out your systems. They mean you start using AI inside the real workflow, not beside it. That’s the difference. You don’t need to understand all the tech. You need to understand where the hours are going and how this could save them.If your team is still bouncing between tabs and pasting text into AI tools, we’ll show you a better way.Start with our<a data-mce-href="https://aistrategyconsulting.com.au/ai-no-code-low-code-implementation" href="https://aistrategyconsulting.com.au/ai-no-code-low-code-implementation"> AI Automation &amp; Implementation </a>we put in play the tools that actually reduce your workload with using these features.<h2>FAQs</h2>Q: What does "multimodal" actually mean? A: It means ChatGPT can take in more than just typed text—it can also see your screen, hear audio, watch videos, and process images all at once.Q: Do I need to install anything? A: No. Screen sharing and live analysis are now part of ChatGPT’s built-in tools (with the right tier). We help clients enable and use them properly.Q: Isn’t that a security risk? A: Not if done right. We help you configure it for privacy, turn off unnecessary access, and keep sensitive data protected.Q: Can this work in a team setting? A: Yes. We’ve built systems where AI observes training calls, writes follow-up notes, and even updates SOPs automatically based on screen activity.

AI Blog

What Google's "AgentSpace" Means for Workflows

How Agentic AI Is Rewriting the Rules of Market Research

How AI Can Speed Up Market Research for Non Techie Teams

How to Use Gen AI For Storytelling and Content Creation

How to Use ChatGPT Canvas to Simplify Your Work

ChatGPT Could Replace Half Your Admin Stack