Business

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

Published

2 months ago

February 21, 2025

AIinAsia

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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Will AI Take Your Job—or Supercharge Your Career?

AI-driven job disruption is already here. Discover practical steps for workers in Asia to stay employable, relevant, and ready for the future.

Published

1 week ago

April 9, 2025

AIinAsia

TL;DR – What You Need to Know in 30 Seconds

Generative AI is already reshaping careers, causing job losses in industries from finance to creative roles.
Workers must continually upskill, strategically plan career moves, and focus on roles AI complements rather than replaces.
Companies and governments must significantly increase retraining efforts to help workers adapt effectively.

Is AI About to Steal Your Job? Here’s How to Stay Ahead in Asia

For many, AI started as a helpful assistant for menial tasks, quick research, or even generating funny memes. But today, it’s taking a serious turn, reshaping industries, displacing jobs, and changing careers overnight.

Just ask Jacky Tan. After thriving for over 15 years as a freelance marketing consultant in Singapore, Jacky found his livelihood disrupted—not just by the pandemic—but by generative AI tools like ChatGPT, which empowered his clients to produce their own content. The result? Jacky, along with countless others, faced a stark choice: adapt quickly or risk becoming obsolete.

Jacky pivoted completely, leaving marketing to open a successful home-based food business, CheekyDon, specialising in Japanese rice bowls. But not everyone can—or will—reinvent themselves so easily. As AI continues to infiltrate the workforce, what can you do to ensure you’re prepared?

Job Disruption: More Real Than Ever

It’s no longer theoretical. Meta, ByteDance, DBS Bank, Grab, and Morgan Stanley have all announced layoffs or workforce reshuffling directly linked to AI-driven efficiencies. Analysts predict as many as 200,000 banking jobs globally could vanish within five years due to AI, highlighting sectors like finance, customer service, risk management, and tech as especially vulnerable.

The numbers don’t lie: The World Economic Forum anticipates 11 million new AI-related jobs globally by 2030—but 9 million existing roles will disappear. And the shift won’t just hit repetitive tasks. Highly skilled roles like writers, programmers, PR professionals, and even legal experts face substantial disruption.

Why AI Displaces Jobs—and Creates New Ones

Here’s the paradox: while AI promises increased productivity, it often leads to job losses because current skills don’t match the needs of new AI-augmented roles. Retraining existing workers is crucial but challenging. In places like Singapore, where skilled workers are scarce, companies struggle to balance the speed of AI integration with retaining talent.

The good news? Jobs involving deep human interactions, emotional intelligence, strategic thinking, or managing AI tools themselves remain safer—for now.

How to Stay Relevant in an AI-Dominated Market

So, how can you protect your career from being displaced by AI? Here are actionable steps tailored for the rapidly shifting Asian job market:

1. Continuous Upskilling Is Non-Negotiable
The days of one-off training are over. Commit to lifelong learning by acquiring skills in AI-related fields, from data analytics to AI management tools. Invest in soft skills—like critical thinking, empathy, and strategic communication—which AI struggles to replicate effectively.

2. Proactively Plan Your Next Career Move
Ask yourself, as EY’s Samir Bedi suggests: “What am I upskilling for?” Plan two or three career steps ahead, not just for immediate skill gaps. Explore lateral career transitions that diversify your skillset, making you versatile across industries.

3. Look for Roles Complemented by AI, Not Replaced by It
Jobs with tasks AI can augment rather than entirely replace—like managing automated systems, strategic marketing, or roles that require significant human touchpoints—are safer bets.

Employers Must Step Up, Too

The responsibility doesn’t rest solely on workers. Companies must actively retrain employees to handle AI disruptions effectively. Currently, only around half of Singaporean workers feel their employers provide sufficient training opportunities. Organisations that actively support their teams through retraining will reap long-term rewards, maintaining both institutional knowledge and market reputation.

Asia’s Workforce at the Crossroads

We’re facing nothing less than the Fourth Industrial Revolution, driven by generative AI. Unlike previous waves of automation, AI can replace tasks once thought too complex or creative for machines. But remember, while AI might take your current role, it also opens doors to entirely new career paths—provided you’re ready to step through them.

Are you prepared to let AI shape your future—or will you shape your own future with AI? Let us know in the comments below!

You may also like:

Young Workers are Embracing ChatGPT
10 ChatGPT Prompts to Ignite Your Business Evolution
You can also learn more at Singapore’s SkillsFuture by tapping here.

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The Three AI Markets Shaping Asia’s Future

Explore the three interconnected AI markets shaping Asia’s technological landscape—traditional AI, training infrastructure, and enterprise solutions—and discover how each drives innovation.

Published

2 weeks ago

April 6, 2025

AIinAsia

TL;DR – What You Need to Know in 30 Seconds

AI isn’t one monolithic market—it’s three interconnected segments:

1. Pre-GenAI (traditional AI): Fundamental techniques that underpin data-driven solutions.
2. AI Training Market: Resource-intensive frontier models driving the next AI breakthroughs.
3. Enterprise AI Market: Real-world applications delivering measurable business outcomes.

Understanding their interplay is critical for Asian businesses aiming to maximise ROI from AI investments.

Are We Missing the Bigger Picture in the AI Race?

From smarter chatbots to insightful analytics, AI’s not one market—it’s three interconnected ones, each shaping how Asia leverages technology.

If you’ve spent any time recently skimming headlines about artificial intelligence, you’d be forgiven for thinking that generative AI is the only show in town. But AI isn’t just ChatGPT, Midjourney, or flashy avatars of celebrities endorsing your new favourite tech gadget. Behind the scenes, three distinct but intertwined markets are at play: the Pre-GenAI Market, the Training Market, and the Enterprise AI Market.

But what exactly are these three markets, and why should Asian businesses care?

Let’s unpack them one by one and understand how they converge to drive the future of innovation across Asia.

1. The Pre-GenAI Market: The Building Blocks of AI

Generative AI may be the current media darling, but the roots of AI go far deeper. We’re talking about traditional AI—technologies like machine learning (ML), reinforcement learning, and computer vision. These foundational techniques have been quietly evolving for decades, long before ChatGPT ever typed out its first response.

Contrary to popular belief, traditional AI hasn’t lost its relevance—far from it. In fact, the rise of generative AI has amplified its importance. Why? Because generative AI feeds on data often produced by traditional AI methods. For instance, Dell Technologies frequently uses machine learning to streamline supply chains or improve factory efficiency. These methods don’t get less important just because GPT-5 is around the corner—they become essential.

In short, traditional AI is like rice in Asian cuisine—fundamental, reliable, and always necessary, no matter what fancy new dish appears on the menu.

2. The Training Market: Powering AI’s Frontier

Next up is the AI training market—think of it as AI’s heavy lifting division. This market is dominated by big names you’ll recognise (OpenAI, Google DeepMind, Nvidia, Meta) who are making gigantic investments in infrastructure to create foundational AI models. Picture rows and rows of servers, massive GPU clusters, and sprawling data centres, humming 24/7.

These frontier models—like GPT-4 or Gemini—require immense computational resources. This isn’t just about bragging rights; it’s about pushing the boundaries of what AI can do. The innovations here spill directly into practical tools businesses use every day, like AI-driven coding assistants or creative platforms for content creation.

In Asia, we’re seeing heavy investment in this market too. Take Singapore’s AI supercomputing initiatives or China’s Baidu and Alibaba building mega-AI clusters. These moves aren’t just technological vanity—they’re strategic investments in the future.

3. The Enterprise AI Market: Real-World Results

And then there’s the enterprise AI market, arguably the most pragmatic of the three. Enterprises aren’t racing to build the next ChatGPT killer. Instead, they’re laser-focused on AI that solves real business problems—like optimising inventory management, enhancing customer support, or boosting marketing effectiveness.

Unlike the flashy training market, the enterprise market moves slower but deliberately. Enterprises demand reliability, compliance, and measurable outcomes—exactly the opposite of the ‘move fast and break things’ mentality we see in frontier AI research.

Across Asia, the enterprise AI market is thriving precisely because it offers clear returns. Banks in Indonesia deploy AI-driven chatbots to handle customer queries efficiently. E-commerce giants in Vietnam and Thailand integrate predictive analytics to forecast inventory and customer demand. It’s AI that’s practical, measurable, and directly linked to ROI.

How These AI Markets Interconnect

Here’s the real takeaway: These three markets aren’t isolated islands; they’re deeply interconnected ecosystems.

Traditional AI gathers and prepares the essential data. The training market produces foundational AI models and cutting-edge tech innovations. Enterprises then integrate both, using these tools and data to transform operations and customer experiences.

Think about it this way: traditional AI builds the roads, the training market crafts powerful engines, and the enterprise market drives the cars, delivering real-world value. Without any one of these, the system falters.

For instance, enterprises use AI-powered data agents to analyse massive datasets prepared by traditional AI methods. They then leverage frontier AI models (like generative AI) trained in data centres to extract actionable insights. The whole system is interdependent—each component driving progress in the other.

Why Does This Matter to Asia?

Asia is a unique melting pot of digital maturity, economic growth, and competitive intensity. Understanding these three markets isn’t just academic—it’s crucial for businesses looking to harness AI’s full potential.

For instance, enterprises in Southeast Asia’s rapidly expanding digital economy (expected to hit $263 billion GMV by 2025 according to Google’s recent e-Conomy SEA 2024 report) need practical AI solutions that deliver immediate business value. On the other hand, countries like Singapore, South Korea, and Japan are leading investments into the training market, building the infrastructure needed to power Asia’s next generation of AI innovations.

Simply put, knowing how these three AI markets interact helps Asian businesses invest smarter, act faster, and innovate effectively.

As we look ahead, Asia is uniquely positioned to benefit from understanding this AI ecosystem deeply. Whether you’re in manufacturing, finance, e-commerce, or healthcare, your business will inevitably interact with all three markets—whether you realise it or not.

Now, here’s something for you to ponder (and comment below!):

Which of these AI markets do you think will dominate Asia’s tech landscape by 2030? Will traditional methods endure, frontier models take over, or will enterprise solutions reign supreme?

We’d love to hear your thoughts.

You may also like:

A Cautionary Tale for Asian Enterprises
Accenture and Nvidia’s AI Power Play in Asia
Perplexity’s Deep Research Tool is Reshaping Market Dynamics
Learn more by tapping here.

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Embrace AI or Face Replacement—Grab CEO Anthony Tan’s Stark Warning

ChatGPT now generates previously banned images of public figures and symbols. Is this freedom overdue or dangerously permissive?

Published

2 weeks ago

April 3, 2025

AIinAsia

TL;DR – What You Need to Know in 30 Seconds

Grab CEO Anthony Tan believes workers and companies that don’t embrace AI risk being replaced by those who do.
Grab paused normal operations for a nine-week generative AI sprint, significantly boosting innovation.
AI tools developed by Grab, such as driver and merchant assistants, are empowering everyday entrepreneurs.
Globally, many companies are downsizing due to AI, but Tan insists AI enhances human capabilities rather than replacing them.

Is Your Refusal to Embrace AI Secretly Sealing Your Fate?

Anthony Tan, co-founder and CEO of Grab—the Southeast Asian super-app that transformed regional transport, food delivery, and financial services—has made a bold and slightly unsettling prediction: “Humans who don’t embrace AI will be replaced by humans who embrace AI.”

In other words, whether you’re a company or an individual, ignoring AI isn’t merely shortsighted—it’s career suicide.

But before we panic, what exactly does Tan mean?

Making Humans ‘Superhuman’

Speaking at Converge Live in Singapore, Tan explained to CNBC’s Christine Tan that AI isn’t just a fancy tech upgrade. Instead, it’s a crucial tool to “make you superhuman” by significantly boosting productivity and freeing up valuable time.

Tan himself isn’t just preaching—he’s practising. Despite not being a coder, he’s enthusiastically using AI coding assistants for personal and professional projects. He claims AI has radically changed his productivity, helping him accomplish things previously impossible.

I can’t code myself, but I use AI to build my own projects, for research, for Grab,” Tan explained. “It totally changes how you spend your time.
Anthony Tan, Grab CEO
Tweet

Grab’s Radical AI Experiment

Grab didn’t stop at encouraging individual AI adoption. Instead, the company took it to a whole new level, implementing an ambitious, company-wide nine-week “generative AI sprint”.

This meant putting all regular business on pause to explore AI-driven solutions across the entire company. As Tan humorously admitted:

People thought I was crazy—maybe I am—but it really moved the needle.
Anthony Tan, Grab CEO
Tweet

During this sprint, Grab developed powerful AI tools, including:

Driver Co-pilot: An AI assistant reducing wait times and boosting job opportunities for drivers.
Merchant AI Assistant: Imagine a single mother in Jakarta now equipped with an AI-driven sous chef, packaging expert, and even a chief revenue officer—all in one assistant. This innovation isn’t just about efficiency; it’s empowerment, reshaping the livelihoods of Grab’s vast network of entrepreneurs.

The Wider Implications for Asia

This isn’t just a Grab-specific phenomenon. According to the World Economic Forum’s 2025 Future of Jobs Report, 40% of employers globally plan to downsize due to AI, and a whopping 86% anticipate AI reshaping their businesses by 2030.

Asia, in particular, with its digitally fluent workforce and vibrant entrepreneurial scene, stands uniquely poised to lead this transition. Grab’s aggressive AI strategy under Tan’s leadership could become a model for businesses across Southeast Asia, showcasing how AI can be harnessed responsibly and productively.

Human vs AI: Not a Zero-Sum Game

Tan stresses AI shouldn’t evoke fear—it should inspire excitement. AI adoption isn’t about machines replacing humans. It’s about humans becoming irreplaceable by effectively harnessing these tools.

If you’re reluctant or sceptical, Anthony Tan’s message is clear: embrace AI now, or watch as those who do leave you behind.

Hot Take

Anthony Tan might sound dramatic—but he has a point. If you’re not actively exploring AI, you’re preparing yourself (and your company) to become obsolete. The clock is ticking: Will you adapt, or will you become the adaptation?