Business
Adrian’s Arena: When Will AI Replace the CMO?
AI is transforming marketing while highlighting the irreplaceable role of Chief Marketing Officers (CMOs) in strategy, creativity, and EQ.
TL;DR
- AI Enhances but Doesn’t Replace CMOs: AI excels at data analysis and automation, but lacks the strategic vision, creativity, and emotional intelligence that CMOs bring to brands.
- AI Empowers Data-Driven Decisions: Machine learning helps CMOs make precise, effective marketing decisions by segmenting audiences and predicting trends.
- CMOs Balance AI with Human Insight: While AI meets Gen Z’s desire for instant gratification, CMOs ensure brands maintain deeper connections and values-driven messages.
Exploring the Possibilities of AI Replacing the CMO
I recently had the fortune to reconnect with an old friend who was travelling through my hometown. Something of an AI skeptic, well at least the impact of AI, we eventually got to pondering the positions of CSuites here in Asia.
With AI now a core part of modern marketing, could AI replace the Chief Marketing Officer (CMO)?
The reach of AI—processing data, automating tasks, personalising messages—is making marketing more efficient than ever. Yet, there’s something deeply human about the qualities a CMO brings to a brand: strategic vision, creativity, and emotional intelligence.
In this article, the first in a series of articles exploring the slightly terrifying closer look at what AI can and can’t do – especially when it comes to the leadership – we will explore whether the role of a CMO, which is required to drive meaningful connections, is one which only a human can truly fulfil. And let’s not forget, Gen Z’s unique approach to brands means the CMO role is only becoming more essential…
AI’s Expanding Role in Marketing: Capabilities and Current Limitations
- Enhanced Capabilities, Not a Replacement: AI brings exciting possibilities for marketers, like being able to sift through huge datasets, automate tasks, and deliver personalised experiences that feel like they’re just for you. CMOs now have more support than ever to make informed decisions, spotting trends faster and refining campaigns in real time. It’s a far cry from the manual analysis days, and it means that CMOs can now spend more time focusing on high-level strategy and creativity rather than number-crunching.
- Data-Driven Decisions with a Personal Touch: The way AI empowers CMOs to be data-driven is unprecedented. With machine learning picking up on subtle consumer behaviours, marketing can be precise and effective. Algorithms help segment audiences down to a granular level, meaning CMOs can target more thoughtfully than ever. Predictive analytics also gives CMOs that valuable ability to get ahead of trends, guiding campaigns with a proactive, rather than reactive, touch.
- Streamlining Campaigns and Automating Customer Interactions: AI has been a game-changer for campaign management and customer interactions. AI-driven platforms handle ad targeting, email campaigns, content personalisation, and customer service automation 24/7, all without breaking a sweat. This allows marketers to focus on the big picture—brand growth, innovation, and creativity—leaving the executional tasks in AI’s capable hands.
Generative AI can even spark new content ideas based on real-time data, but when it comes to defining the “why” behind a campaign, only a human CMO has the vision to make it resonate.
The Evolving Responsibilities of CMOs in an AI-Driven Landscape
Leading AI Integration with Innovation
Today’s CMO isn’t just responsible for traditional marketing; they’re at the forefront of adopting AI and blending it seamlessly into the marketing strategy. Getting it right means balancing what AI offers with the brand’s voice and values. AI is powerful, but without careful oversight, it can lose sight of what makes a brand unique.
Creativity and Automation in Tandem
While AI excels at the technical stuff—analysing data, segmenting audiences, automating repetitive tasks—it simply doesn’t have the creative intuition or emotional intelligence that makes a brand truly memorable. A CMO’s creativity involves cultural understanding, subjective decision-making, and an ability to weave the brand’s unique personality into every campaign.
As AI takes on more routine tasks, CMOs are doubling down on creativity to ensure the brand feels consistent, authentic, and connected to its audience.
Upskilling the Marketing Team
As AI becomes central to marketing, CMOs have an important role in upskilling their teams. Experimentation, learning, and adaptability are essential mindsets as marketers embrace new tools and methodologies. A CMO fosters a team culture that values continuous learning, empowering marketers to embrace the potential of AI rather than fear it.
Understanding Gen Z’s Transactional Nature and AI’s Role
- Instant Gratification and Transactional Expectations: Gen Z and Gen Alpha are changing the marketing game. They value speed and efficiency, often more than brand loyalty itself. For them, convenience and authenticity go hand in hand, and they don’t want to be kept waiting.
- Seamless: AI is ideal for delivering these seamless, hyper-personalised experiences, making interactions as quick and efficient as Gen Z expects.
The CMO’s Balancing Act: Speed and Substance
AI may deliver efficiency, but CMOs know it’s crucial not to lose the substance that makes a brand meaningful. While AI meets Gen Z’s desire for instant gratification, it can’t create the deeper connection that leads to brand loyalty. Gen Z are also incredibly socially conscious; they want brands to be clear about their values and stand for something beyond profit.
Here, the CMO is pivotal in ensuring the brand message is values-driven, adding layers of meaning and purpose to AI-driven interactions.
Using AI to Craft Values-Driven Messages
AI can gather insights into Gen Z’s preferences and behaviours, helping CMOs create messages that speak to these values without compromising on speed and personalisation. By blending AI’s strengths with human insight, CMOs deliver not just efficiency, but authenticity and relevance—qualities that keep Gen Z engaged and invested.
Could AI Replace the CMO or the Marketing Team? The Future of Marketing Roles
Automating Execution, Not Strategy
Many traditional marketing tasks—customer segmentation, ad targeting, A/B testing, and even some content creation—are increasingly automated by AI. Tools that personalise customer journeys or generate content on the fly make these tasks easier, but they’re still not a substitute for human insight.
AI may streamline execution, but it’s the CMO’s strategic vision that brings these campaigns to life.
Data Analysts and Market Researchers
AI is excellent for crunching numbers, but it needs the human touch to interpret those findings meaningfully. Human analysts bring a contextual understanding to data that AI lacks, especially in fast-changing markets where intuition and experience are invaluable.
The Creative Team
While AI can support design, copywriting, and content production, it doesn’t replace the creative direction, cultural awareness, or originality that human creatives provide. Generative AI tools are amazing for sparking ideas or suggesting variations, but a brand’s story needs human depth and originality. Creatives add the layers that make a campaign resonate.
AI Limitations in Cross-Cultural Contexts
When marketing across diverse regions, understanding cultural nuances is essential. AI can pick up on trends, but without context, it can misinterpret behaviours. A campaign that resonates in one market may fall flat in another. Human marketers bring that cultural sensitivity, shaping messages to suit different contexts.
Marketing Strategists and Campaign Planners
AI can provide valuable insights and data, but it doesn’t understand the creative risk or brand values that go into planning a campaign. Human strategists interpret AI-driven insights to craft cohesive campaigns that go beyond audience segmentation, fostering real connections and brand affinity.
The Hybrid Model: Humans and AI in Harmony
The future of marketing will likely be a blend of AI-driven efficiency and human creativity. AI will handle data-heavy and routine tasks, giving marketing teams the time to focus on big-picture strategy and storytelling.
6 Key Challenges in AI Integration for CMOs
- 1. Data Quality and Management: AI relies on accurate data, but fragmented or inconsistent data can lead to flawed insights. CMOs need solid data management practices to ensure AI has reliable information, and they need to address privacy and compliance concerns to maintain consumer trust.
- 2. Closing the Skills Gap: As AI tools become more common, CMOs face a gap in AI marketing skills within their teams. Closing this gap requires a commitment to learning and a culture that encourages experimentation with AI tools. Upskilling is crucial to make the most of AI’s capabilities.
- 3. Choosing the Right Tools: The abundance of AI tools can be overwhelming. CMOs must find the tools that align with the brand’s needs, integrate with existing systems, and enhance workflows rather than complicate them. It’s all about finding what fits.
- 4. Balancing AI Insights with Creativity: AI can suggest creative elements that perform well, but if we rely on it too much, we risk creating campaigns that all feel the same. The CMO ensures there’s a balance, using AI to guide decisions while keeping the brand’s originality intact.
- 5. Ethical AI Use: Consumers expect brands to use AI responsibly. CMOs have to establish clear ethical guidelines for AI, including regular audits to check for biases and ensure the brand remains trustworthy and fair.
- 6. Proving ROI: AI implementations aren’t cheap, so demonstrating ROI is vital. CMOs need to set measurable goals for each AI tool, ensuring that every investment in AI supports the brand’s strategic objectives.
Strategies for Effective AI Integration in Marketing
- Encouraging Experimentation: CMOs can foster a culture of experimentation, encouraging teams to try AI tools and see what works. It’s all about learning through testing and allowing room for innovation.
- Maintaining Data Integrity and Morals: Strong data practices are essential for effective AI. Regular checks for accuracy and bias, plus transparent AI use, help maintain consumer trust and brand credibility.
- Phased AI Adoption: Gradual implementation allows teams to get comfortable with AI tools without overwhelming them. Starting small and scaling up based on feedback and results ensures AI adoption is smooth and effective.
- Cross-Departmental Collaboration: Effective AI use involves teamwork across departments. Working closely with IT, legal, and data science teams ensures AI adoption aligns with compliance and tech requirements, creating a streamlined experience for everyone.
Why Humans Are Ultimately Irreplaceable in a CMO Role
- Big-Picture Thinking and Brand Leadership: A CMO’s strategic vision goes beyond data and metrics. They set the direction for the brand, ensuring all marketing aligns with the company’s goals and values. AI may help execute, but it doesn’t guide or inspire.
- Empathy and Creativity: CMOs understand what motivates consumers on a personal level. This empathy, combined with a creative touch, turns data into stories that resonate emotionally. AI can support creativity, but it can’t fully replace the empathy that brings campaigns to life.
- Adaptability and Context: Markets change fast, and a CMO’s ability to adjust campaigns to fit new cultural trends or societal changes keeps the brand relevant. AI depends on past data and often struggles to adapt to the new, something a CMO does with ease.
So What Does This All Mean… Will AI Replace the CMO Role?
Human qualities like creativity, emotional intelligence, and strategic oversight are what truly connect brands with people.
The future of marketing is a collaborative one, where AI enhances human insight to create campaigns that are not only effective but meaningful.
Join the Conversation
What do you think about the future of AI in marketing? How do you see the role of CMOs evolving with advancements in AI? Share your thoughts in the comments below and subscribe for updates on AI and AGI developments here. We’d love to hear your insights!
You may also like:
- AI Content: A Ticking Time Bomb for CMOs?
- The AI Takeover: Which Jobs Are First in Line?
- Adrian’s Arena: AI is Shaping the Future of Marketing to Gen Z in Southeast Asia
- Try AI for yourself on ChatGPT by tapping here
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Perplexity’s Deep Research Tool is Reshaping Market Dynamics
Perplexity’s Deep Research tool is challenging premium AI subscriptions by offering advanced research capabilities at a fraction of the cost
TL;DR – What You Need to Know in 30 Seconds
- Perplexity’s Deep Research tool offers advanced AI research capabilities for a fraction of typical enterprise costs.
- It provides five free queries daily and charges $20 per month for 500 queries—compared to big AI providers charging thousands.
- Scored 93.9% on SimpleQA and 20.5% on Humanity’s Last Exam, outpacing Google’s Gemini Thinking, with OpenAI only slightly higher at 26.6%.
- Enterprise AI spending is projected to rise by 5.7% in 2025, although some companies are increasing their AI budget by 10% or more.Deep Research could shift the market by making companies question premium AI subscriptions that cost up to 100x more.
- The tool handles a range of tasks (healthcare, finance, market research) in under three minutes, democratising AI for smaller businesses and individuals.
- This affirms a new era in AI, where affordability meets performance, and big spenders must now justify their exorbitant costs.
Unpacking Perplexity Deep Research Tool, and its Impact
Today, we’re diving into one of the most talked-about innovations in AI right now: Perplexity’s new Deep Research tool. If you haven’t heard of it yet, don’t fret—this is precisely what we’re here for. Grab your favourite cuppa, because we’re about to explore how Perplexity is turning AI research upside down, smashing cost barriers, and making us question every pricey AI subscription that’s ever crossed our desks. Sound good? Let’s get stuck in!
The Big Bang of Affordable AI
You know how some products come along and make you wonder why you ever paid so much for something else? That’s exactly what’s happening with Perplexity’s Deep Research. In a single, bold move, Perplexity has basically told the rest of the AI industry: “We’re here, we’re cheap, and we’re not messing about.” If you haven’t caught wind of it, Deep Research is a tool that can generate comprehensive research reports in just minutes. Yes, minutes. And here’s the kicker: it offers advanced AI capabilities at a fraction of the typical enterprise costs.
Take a look at what’s on the table: while Anthropic and OpenAI can easily charge into the thousands every month for their premium services, Perplexity is throwing in five free queries daily for all users and an upgrade at $20 per month for 500 daily queries plus faster processing speeds. That’s not just cheaper; it’s borderline scandalous when you see that other AI giants charge almost 100 times more for near-similar (and, in some cases, arguably lesser) capabilities.
But it’s not just a marketing gimmick. Aravind Srinivas, Perplexity’s CEO, shared the company’s ethos on X (formerly Twitter), saying, “Knowledge should be universally accessible and useful. Not kept behind obscenely expensive subscription plans that benefit the corporates, not in the interests of humanity!” It’s hard not to be inspired by that. The democratisation of AI has long been touted as the Next Big Thing in tech, but Perplexity is making some serious strides to actually achieve it, rather than just talk about it.
Deep Research is now a commodity thanks to Perplexity pic.twitter.com/Fk8yvPTLzV— Aravind Srinivas (@AravSrinivas) February 14, 2025
Enterprise AI Spending Under the Microscope
As you might guess, this sudden plunge in price is raising eyebrows—big time. Large enterprises have been funnelling massive budgets into AI, with some expecting to increase their AI spending by 5.7% in 2025. That’s despite overall IT budgets going up by less than 2%. In certain sectors, that surge in AI spending could be as high as 10%, and on average, some businesses plan to throw in an additional $3.4 million into AI initiatives. With the rise of Deep Research, though, those expensive subscriptions now look a little, well, questionable.
Let’s be real. When you’ve got a brand-new AI tool that gives near-enterprise level performance (and sometimes even more advanced capabilities) for $20 a month, it begs the question: What are we actually paying for with those premium AI subscriptions? If you’re on the corporate side, you might be reviewing your budgets as we speak. Think about the training, the data hosting, the staff overhead—yes, those are real costs. But are they enough to justify a 100x difference in price?
Technical Mastery That’s Giving Giants a Run for Their Money
Now, let’s talk numbers, because who doesn’t love a good metric? Perplexity’s Deep Research scored a whopping 93.9% accuracy on the SimpleQA benchmark and clocked 20.5% on Humanity’s Last Exam. If you’re wondering why that second number is interesting, consider that it outperforms Google’s Gemini Thinking and other top-tier models. Even more eyebrow-raising is that OpenAI scores 26.6% on Humanity’s Last Exam—yes, that’s higher than Perplexity’s 20.5%—but let’s not forget the monstrous cost difference for that extra 6 percentage points.
Perplexity also claims that Deep Research completes most tasks in under three minutes, performing dozens of searches and analysing hundreds of sources simultaneously. That’s lightning-fast by any measure, especially when you realise it’s essentially replicating what expert human researchers would do—but in a fraction of the time. For advanced tasks like financial analysis, market research, technical documentation, or even healthcare insights, it’s an absolute game-changer.
Why This Matters to You (and Everyone Else)
Alright, it’s cheap, it’s fast, and it’s accurate. Who cares, right? Well, pretty much anyone who’s ever wanted to make use of advanced AI capabilities but balked at the price tag. It’s no secret that enterprise AI has often ended up creating a digital divide: if you’ve got the budget, you can do some serious data-crunching, but if not, you’re left in the dark ages. This means smaller businesses, individual researchers, students, or freelancers could only dream of some of these AI services because they couldn’t justify the cost.
But along comes Perplexity, democratising the whole playing field. The potential is enormous. If you’re a small tech start-up, you no longer have to pay thousands just to get your data insights. Researchers can use Deep Research for thorough academic or industry analyses. Professionals in healthcare or finance can produce detailed reports that would usually cost an arm and a leg. And because Perplexity plans to expand Deep Research to iOS, Android, and Mac platforms, access is only going to get easier.
Is Enterprise AI in for a Shake-up?
If you’re in charge of procurement or strategic decisions for a big firm, your job just got a bit more complicated. Do you stick with the big-name provider with that hefty subscription fee, or do you try Perplexity to see if it meets your organisation’s needs? The key question is: Are you really getting the added value for your money when your monthly AI bills are in the thousands?
Sure, there could be a few reasons to keep paying extra. Perhaps you’re already deeply integrated with a certain AI ecosystem, or you need custom solutions that only a big player can provide. Maybe you rely on dedicated customer support that’s included with your pricy subscription. But the argument that premium cost automatically translates to premium capability is quickly losing steam.
With Perplexity’s impressive performance, we might see a future where expensive enterprise AI tools have to scramble to prove they’re worth it. You can’t just plaster “enterprise-grade” on a service and watch the money roll in—users want tangible, cost-effective results.
How Deep Research Outperforms (and Where It May Still Lag)
Let’s not gloss over the fact that OpenAI’s own research capabilities still technically inch out ahead in certain benchmarks. A 26.6% score on Humanity’s Last Exam compared to Perplexity’s 20.5% might be a big deal for mission-critical tasks in specialised domains. Then again, Perplexity’s 93.9% on SimpleQA is hardly peanuts. And let’s remember the price difference—OpenAI can charge hundreds (if not thousands) of percent more. So is that extra 6 percentage points in performance worth the colossal increase in cost?
It all boils down to your use case. If you’re a hedge fund manager who needs the absolute best of the best and every fraction of a percent could mean millions in revenue, you might still throw your money at the top-of-the-line model. But if you’re a mid-sized firm or an independent researcher, Perplexity’s offering is more than enough—especially at $20 a month.
Practical Implications: From Healthcare to Finance
Let’s look at some real-world scenarios. Healthcare professionals can use Deep Research to scour medical journals, clinical trial results, and official guidelines faster than you can say “NHS queue”. This means better patient outcomes, quicker insights, and less reliance on massive IT budgets.
Financial analysts can crunch market data, follow the latest economic news, and whip up in-depth reports that previously needed entire teams of well-paid data scientists. Technical documentation tasks become a breeze when Deep Research can parse through troves of manuals, development forums, and official documents in minutes.
Plus, Perplexity’s user-friendly features—like exporting findings as PDFs or sharing them directly through its platform—make collaboration straightforward. If you’ve ever had to wrestle with clunky enterprise software, you’ll appreciate the simplicity that Perplexity offers.
The Democratisation Ripple Effect
We’ve talked about how smaller entities stand to benefit from cheaper AI tools. But let’s not forget the social dimension. When you lower the barrier to entry, you empower not just businesses, but also students, civil society organisations, journalists, and independent researchers. Knowledge stops being locked behind corporate walls. That’s a big deal in Asia—where the digital transformation wave is sweeping nations at very different speeds and scales.
Imagine an NGO in a rural part of Southeast Asia that can now access top-notch AI research capabilities for $20 a month. That’s a giant leap forward in bridging the digital gap, enabling them to better serve local communities, gather data, and deliver more effective programmes. It’s not just a business story; it’s a social justice story too.
What’s Next in 2025 and Beyond?
Given that AI spending is expected to rise by 5.7% in 2025, the question on everyone’s lips is how this new wave of budget-friendly AI offerings will redistribute the market. Will companies continue throwing millions at established AI giants, or will they pivot to nimble, cost-effective alternatives like Perplexity?
In many ways, this sets the stage for an AI arms race of affordability and performance, where large players need to prove they’re worth the extra cash—or risk losing market share. From what we’re seeing, the AI community (and the public) are hungry for an open-source, reasonably priced alternative. Perplexity’s decision to offer a free daily query allowance and then a generous 500 queries a day for a mere $20 might be the blueprint for the future of AI subscription models.
The Jury’s Verdict and a New Era
So, does this mark the end of expensive AI subscriptions? We’ll have to wait and see. But one thing is clear: Perplexity’s Deep Research has seriously called into question the notion that you need to pay through the nose for quality AI. If performance is almost on par with more expensive services, or in some benchmarks better, why wouldn’t you jump on board?
Perhaps the biggest indicator of success will be user adoption. And it’s already looking promising—thousands of folks have begun testing Deep Research, singing its praises, and pondering whether they really need those thousand-dollar monthly fees. In the dynamic, ever-shifting AI world, the best technology won’t be the one with the biggest marketing budget but the one that’s truly accessible to the people who need it most.
There you have it, folks: a whirlwind tour of how a single innovation from Perplexity is rattling the foundations of AI’s business model. Whether you’re a budding researcher, a startup founder, or a corporate decision-maker, the paradigm is changing right before your eyes. Will you be part of the revolution—or left clinging to yesterday’s overpriced subscriptions? The choice, as always, is yours! And don’t forget to subscribe to keep up to date with all the latest AI happenings in Asia.
What Do YOU Think?
As AI costs plummet and quality soars, will businesses continue to pay premium prices out of habit—or dare to embrace the affordable future? Let us know in the comments below!
You may also like:
- Perplexity Deep Research Tool Debuts, Challenging OpenAI and Google
- Perplexity Assistant: The New AI Contender Taking on ChatGPT and Gemini
- Or try Perplexity AI by tapping here.
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Microsoft 365 Copilot Chat: AI Productivity Without the Subscription
Microsoft 365 Copilot Chat brings free AI-powered chat and pay-as-you-go AI agents to businesses, offering flexible task automation without a full subscription. Discover how it works, pricing details, and whether it’s right for you.
TL;DR – What You Need to Know in 30 Seconds
- Microsoft 365 Copilot Chat introduces free AI-powered chat with GPT-4 and pay-as-you-go AI agents for automating business tasks.
- Key features: Market research, document summarisation, real-time collaboration, AI-generated images, and file uploads.
- Pay-as-you-go AI agents automate repetitive tasks, billed at $0.01 per message or $200 for 25,000 messages/month.
- Enterprise-grade security & IT controls ensure data protection, agent governance, and compliance with company policies.
- Difference from Microsoft 365 Copilot: Copilot Chat offers a free entry point, while Microsoft 365 Copilot provides deep integration and personalised AI assistance for $30 per user/month.
Microsoft 365 Copilot Chat: Free AI Chat with Flexible AI Agents
Microsoft has expanded its AI-powered productivity offerings with Microsoft 365 Copilot Chat, an enhanced chat solution powered by GPT-4. Unlike the premium Microsoft 365 Copilot, which requires a monthly subscription, Copilot Chat offers a free chat experience with optional pay-as-you-go AI agents. This model makes AI-powered automation more accessible to businesses while maintaining enterprise-grade security and IT control.
What’s New in Microsoft 365 Copilot Chat?
Copilot Chat provides a secure, AI-powered assistant that can handle everything from market research and strategy development to content creation and file analysis. Key features include:
✅ AI-Powered Chat (Free)
- Secure chat powered by GPT-4 for research, strategy documents, and meeting preparation.
- File uploads allow users to summarise reports, analyse Excel spreadsheets, and improve presentations.
- Copilot Pages enables real-time collaboration between humans and AI.
- AI-generated images for campaigns, product launches, and social media posts.
✅ Pay-As-You-Go AI Agents
- Task automation: Agents can be created via natural language prompts to handle repetitive tasks.
- Flexible pricing: $0.01 per message or $200 for 25,000 messages/month via Microsoft Azure.
- Enterprise IT controls: IT admins manage agent deployment and permissions via Microsoft Copilot Studio.
✅ IT & Data Protection Features
- Enterprise Data Protection (EDP): Ensures uploaded content isn’t used to train AI models.
- Copilot Control System: Governs agent access, usage, and security policies.
- Access control & monitoring: IT teams can track agent interactions and adjust permissions.
Copilot Chat vs. Microsoft 365 Copilot: What’s the Difference?
While both solutions leverage AI, Copilot Chat offers an on-demand AI assistant, whereas Microsoft 365 Copilot provides a deeply integrated AI experience. Here’s how they compare:
Feature Microsoft 365 Copilot Chat Microsoft 365 Copilot Pricing Free chat, $0.01 per agent message $30/user/month AI Model GPT-4, web-grounded chat GPT-4, integrates with Microsoft 365 apps Document Uploads & Analysis ✅ ✅ AI Image Generation ✅ ✅ Agent Automation ✅ (Pay-as-you-go) ✅ (Subscription-based) Microsoft 365 App Integration ❌ (Limited) ✅ (Full access) Enterprise IT Controls ✅ ✅ (More advanced controls)
How Businesses Can Benefit from Copilot Chat
💡 Lower Cost, Higher Flexibility:
Companies can use free AI chat and only pay for AI agents when needed—ideal for businesses that don’t require a full Microsoft 365 Copilot subscription.
💡 Task Automation for Teams:
Teams can automate manual, repetitive workflows with AI agents, optimising efficiency without major IT infrastructure changes.
💡 Enterprise-Grade Security & Control:
IT admins can manage AI agent permissions, ensuring compliance and governance over data access and automation tools.
How to Get Started with Copilot Chat
1️⃣ Enable Free AI Chat: Available by default for Microsoft 365 commercial customers via Microsoft365.com/copilot.
2️⃣ Use AI Agents (Optional):
- Free agents (based on public data and uploaded files) are enabled via Microsoft 365 Admin Center.
- Paid agents require a Copilot Studio subscription via the Power Platform Admin Center (PPAC).
3️⃣ Choose Your Pricing Model: - Pay-as-you-go: $0.01 per message (billed via Azure).
- Capacity packs: $200 for 25,000 messages/month.
4️⃣ Manage and Monitor Agents: IT admins can monitor usage, trends, and performance through Microsoft Copilot Studio.
Final Thoughts: A More Flexible AI Assistant for Businesses
Microsoft 365 Copilot Chat represents a shift towards AI accessibility and flexibility, offering both free AI-powered chat and on-demand automation. While Microsoft 365 Copilot remains the go-to solution for businesses deeply embedded in the Microsoft ecosystem, Copilot Chat provides a cost-effective alternative for those seeking AI-powered efficiency without a full subscription commitment.
For businesses looking to streamline workflows, automate tasks, and leverage AI without long-term contracts, Copilot Chat’s pay-as-you-go agents offer a compelling alternative to traditional AI subscriptions.
Let’s Talk AI!
How are you preparing for the AI-driven future? What questions are you training yourself to ask? Drop your thoughts in the comments, share this with your network, and subscribe for more deep dives into AI’s impact on work, life, and everything in between.
You may also like:
- Microsoft’s AI Agents Set to Transform Asian Workplaces
- Everyday Hacks with Google and Microsoft AI Tools
- The AI Age is Here—But Can You Ask the Right Questions?
- Try Microsoft Copilot Chat now by tapping here.
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ByteDance’s $12 Billion Investment in AI Infrastructure Set for 2025
ByteDance plans to invest over $12 billion in AI infrastructure in 2025 to enhance global model training capabilities with Nvidia chips.
TL;DR:
- ByteDance is planning to invest over $12 billion in AI infrastructure in 2025, with $5.5 billion allocated for AI chips in China and $6.8 billion dedicated to enhancing model training capabilities internationally.
- This move is aimed at strengthening ByteDance’s AI prowess to stay competitive against Chinese tech giants like Baidu, Alibaba, and Tencent.
- The investment includes a significant focus on acquiring Nvidia chips to bolster global AI initiatives.
If you’ve been keeping an eye on the tech world, ByteDance—the mastermind behind TikTok—is making headlines again. This time, they’re gearing up for a colossal $12 billion investment in AI infrastructure in 2025, according to the Financial Times. Let’s break down what this means and why it’s a big deal.
The Investment Breakdown
ByteDance’s ambitious plan involves:
- $5.5 billion on AI chips in China: This substantial investment is set to double their spending from the previous year, highlighting a strong commitment to enhancing domestic AI capabilities.
- $6.8 billion to boost global model training capabilities: A significant portion of this budget is earmarked for acquiring advanced Nvidia chips, underscoring ByteDance’s strategy to leverage top-tier technology for AI model training.
Why This Matters
- Elevating AI Capabilities: With this hefty investment, ByteDance aims to elevate its AI infrastructure, ensuring that platforms like TikTok continue to offer cutting-edge features and personalised user experiences.
- Staying Ahead in the AI Race: In the fiercely competitive tech landscape, this move positions ByteDance to keep pace with, or even outpace, rivals such as Baidu, Alibaba, and Tencent, all of whom are making significant strides in AI development.
- Strategic Partnerships: By investing heavily in Nvidia chips, ByteDance is aligning itself with a leader in AI hardware, which could lead to more advanced and efficient AI models powering its platforms.
The Bigger Picture
This investment isn’t just about staying competitive; it’s about setting the stage for the future. As AI continues to evolve, companies that invest in robust infrastructure and cutting-edge technology will be better positioned to lead the market. ByteDance’s substantial commitment to AI underscores its vision to be at the forefront of this technological revolution.
Final Thoughts
ByteDance’s planned $12 billion investment in AI infrastructure is a bold move that signals its intent to lead in the AI-driven future. By focusing on both domestic and international advancements and partnering with industry leaders like Nvidia, ByteDance is not just keeping up with the competition—it’s setting the pace.
What are your thoughts on ByteDance’s massive AI investment? Let’s discuss in the comments below.
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