
Predictions 2025: The year ahead for media
Let's call 2024 what it really was, an intense year for the media industry when buzzwords such as artificial intelligence, automation and martech dominated our conversations and challenged the core of our business and the purpose of our craft.
This intensity was felt throughout the year leading up to December when the news of the Omnicom-IPG merger was announced – a move that signals the dawn of a new era in media.
These defining moments of the past year now serve as powerful indicators of the transformative trends shaping 2025.
The scale imperative
We're entering an era when size isn't just about market leverage – it's about survival. The proliferation of platforms and solutions has created a labyrinth of complexity that only the most resourced organisations can successfully navigate.
Major holding groups have responded by architecting ambitious technological roadmaps and data strategies, backed by significant investments in engineering talent and data partnerships.
The competitive advantage of an agency's size in terms of trading power – which seemed to matter less in the previous era – has paved the way to something more fundamental: the ability to sustain investment in transformative tools that can decode our increasingly complex ecosystem.
Gaming, set, go
While gaming has long flirted with mainstream marketing, 2025 marks its decisive breakthrough. The past year saw brands move beyond casual interest to structured strategy, recognising gaming's underutilised potential as a marketing channel.
Current advertising revenue in gaming hovers around 15 per cent, where the overall growth is at 2.1 per cent a dramatic slowdown from the 7 per cent surge during pandemic years. This deceleration has catalysed an aggressive push by major players to forge deeper brand partnerships and pioneer innovative solutions.
The stage is set for gaming to emerge from the shadows of experimental budgets to become a cornerstone of media strategy.
The conversational revolution
The evolution of brand-consumer communication has transcended traditional boundaries. What began as simple messaging apps has matured into sophisticated platforms where brands can listen, learn and respond with unparalleled intelligence and personalisation.
With 80 per cent of businesses already embracing some form of conversational marketing – from straightforward WhatsApp interactions to rich commerce experiences – 2025 marks a pivotal moment when not only does iOS now support the RCS messaging standard, but also AI elevates these exchanges from mere transactions to meaningful relationships.
This isn't just about automation; it's about augmenting human connection with machine intelligence, creating conversations that are not only immediate but deeply relevant and emotionally resonant.
From noise to precision
Back in 2023, Mark Ritson declared that 'synthetic data is suddenly making very real ripples' and while applications like ChatGPT were still in 'toy stage', he foresaw massive implications for marketing. Fast-forward to 2025, where AI-powered tools have evolved beyond simple data generation to create 'synthetic audiences' – sophisticated models that mirror real consumer behaviours and preferences with unprecedented accuracy.
This breakthrough particularly resonates in regions grappling with limited data resources and audience research services. Through advanced machine learning and AI APIs, we can now simulate audience behaviour, predict responses and craft adaptive campaigns that eliminate traditional data biases.
The result reinforces 'the scale imperative' idea: precision targeting that combines intelligence with scalability, fundamentally reshaping how we understand and engage our audiences.
The new tourism paradigm
The convergence of events and tourism has created a powerful new paradigm in destination marketing. Major festivals, sporting events and celebrations have evolved from mere attractions into catalysts for sustained tourism growth.
Events such as the Dubai Shopping Festival, Riyadh Season and landmark occasions like the recent Coldplay concerts in Abu Dhabi have set the stage for even grander moments – Saudi Arabia's Expo 2030 and the 2034 FIFA World Cup – both of which promise to reshape the tourism landscape.
These events are more than just entertainment; they're cultural currency in our social media-driven world, turning Instagrammable moments into powerful personal branding tools. The real value lies in the data they generate, enabling hyper-personalised campaigns that transform fleeting experiences into lasting brand connections, ultimately shaping the future of experiential tourism.
In this era of rapid change and heightened expectations, brands that master the art of blending intelligence with authenticity will lead the way. Success within media in 2025 won't just come from adapting to trends, but from turning complexity into clarity, noise into impact and transient moments into enduring strategies.
By Joe Nicolas, CEO, UM MENAT

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Crypto Insight
5 hours ago
- Crypto Insight
How to use Grok for real-time crypto trading signals
Grok scans real-time sentiment on X to detect early crypto trends, including meme coin momentum and macro reactions. Traders have used Grok-style setups to track tokens like TURBO, ORDI and FET before price moves occurred. Unlike chart-based tools, Grok captures emotional tone and crowd narrative shifts across thousands of posts. When paired with ChatGPT, Grok helps surface signals, while ChatGPT assists in strategy design and automation logic. While useful for sentiment parsing, Grok doesn't execute trades, interpret charts or manage risk — it works best as a signal assistant. Many retail traders still rely on news alerts, influencer posts or Discord trading groups to stay ahead of the market . While these sources can offer signals, they're often delayed or shaped by social bias. In fast-moving crypto environments, that delay can mean missing the window to act. Grok, the conversational AI developed by Elon Musk's xAI and embedded into X, is being explored by some traders as a way to monitor sentiment shifts more efficiently. Unlike traditional tools, Grok has direct access to live X data, enabling it to interpret real-time conversations, track trending token mentions, and detect early signs of narrative movement. Some developers are testing Grok in conjunction with other AI tools to surface high-frequency mentions or emotional keywords tied to memecoins and altcoins . One post in a crypto dev forum describes an experimental setup where Grok flagged repeated FLOKI mentions from verified users shortly before a price move. While still experimental, these use cases show how sentiment parsing on X can inform short-term trading decisions. Instead of acting as a trading strategy on its own, Grok is being used as a tool to enhance awareness of market mood, especially for assets driven more by social engagement than fundamentals. What is Grok? Grok is a conversational AI model developed by xAI, Elon Musk's artificial intelligence company. It is currently available to X Premium+ users, where it integrates with the X platform to provide direct access to trending content and public conversations in real time. Unlike traditional AI assistants like ChatGPT, which rely on processed or external data feeds, Grok can tap into live user discussions, sentiment flows and viral trends as they unfold. This makes it particularly useful for tracking crypto sentiment, especially for assets that react to narrative momentum, including memecoins, altcoins and even Bitcoin during key macroeconomic events. Why Grok matters for crypto traders Let's break it down with a real-world scenario: On March 13, 2024, Musk posted a meme featuring Pepe the Frog. Shortly afterward, the price of the Pepe cryptocurrency jumped by 12.2%, breaking the $0.000009 mark. While this timing drew attention, it's important to note that correlation doesn't imply causation. The price movement may have been influenced by broader memecoin activity, technical setups or other social factors, not just the meme post itself. By the time the news reached Telegram groups and aggregators, the entry window had already passed. Now imagine Grok: Reading that influencer's post instantly Parsing community replies to determine sentiment polarity Matching it to previous patterns of similar pump setups Triggering a 'high social spike' alert for meme coins. Traders have begun experimenting with Grok for sentiment-driven trading setups by connecting it to real-time X data via unofficial APIs or scraping tools. Spikes were defined as a 5x increase in token mentions over a four-hour period across verified or high-engagement accounts, while hints included repeated mentions of partnership rumors, macro triggers or keyword anomalies like 'rate cut' or 'whale buy' linked to specific tokens. How to use Grok for sentiment, signals and macro insights If you've traded crypto during a meme cycle, you know how fast sentiment shifts and how slow most tools are to pick it up. Grok changes that. Thanks to its direct integration with X, it can scan thousands of posts, hashtags and comment threads as they happen. When used strategically, Grok becomes a tool not just for reading sentiment but for trading it. Here's how crypto traders are starting to use Grok in practical ways. Sentiment monitoring in real time Grok actively scans crypto posts on X for market-moving phrases and sentiment anomalies, such as 'floor is in,' 'massive unlock,' 'whale dump' or 'rate cut confirmed.' It goes beyond surface-level mentions to decode context, emotional tone and intent in each post. By leveraging X's API, some traders are experimenting with Grok to: Track early sentiment in lesser-known tokens before price action begins: In April 2024, mentions of TURBO increased across X, driven by developer discussions and previews of upcoming features. This shift preceded a 22% price rally roughly 36 hours later, suggesting sentiment tools can expose momentum ahead of chart-based signals. In April 2024, mentions of TURBO increased across X, driven by developer discussions and previews of upcoming features. This shift preceded a 22% price rally roughly 36 hours later, suggesting sentiment tools can expose momentum ahead of chart-based signals. Gauge emotional volatility around macro news events: During the March 2024 US Federal Open Market Committee update, Grok-powered setups flagged rising anxiety around BTC. Traders noted that crowd sentiment turned negative before the actual dip occurred, helping some adjust positioning earlier than usual. During the March 2024 US Federal Open Market Committee update, Grok-powered setups flagged rising anxiety around BTC. Traders noted that crowd sentiment turned negative before the actual dip occurred, helping some adjust positioning earlier than usual. Spot sentiment divergence, where engagement rises but price lags (or vice versa): In February 2024, community chatter around FET spiked, while the price remained flat. Some early traders used this mismatch as an entry cue, preceding a breakout two days later. Unlike traditional keyword scanners, Grok applies deep sentiment parsing and real-time X integration, capturing nuance during high-impact events like Consumer Price Index (CPI) drops, exchange-traded fund (ETF) rumors or influencer U-turns. Below is an example output from a custom sentiment parser built using Grok's access to X, analyzing 12 posts about Bitcoin in a six-hour window. The data set included posts from high-profile accounts like Whale Alert and Michael Saylor, as well as smaller influencers commenting on BTC leverage, short-term trading and macro comparisons. The goal was to measure the emotional and directional tone of real-time crypto sentiment during a volatile trading session. X feed signal parsing Thanks to its integration with X, Grok can detect momentum the moment certain content begins trending. Traders experimenting with Grok-like setups use it to: Track token mentions gaining traction, such as sudden increases in usage of a specific ticker (e.g., '$FET' or '$TURBO') across multiple verified or active accounts within a short window. Monitor influencer activity tied to specific tokens, such as when a high-following account hints at a listing, partnership or price outlook, especially when combined with above-average engagement like repost surges or rapid reply chains. For example, during a 24-hour window in February 2024, the number of posts mentioning '$ORDI' jumped to over 400 from under 50, led by influential traders discussing potential listings. Grok-style sentiment tools flagged this spike in narrative velocity well before price reflected the attention. By analyzing these types of real-time social signals, Grok enables users to spot early momentum shifts across crypto communities. This allows traders to evaluate developing narratives while they're still taking shape rather than reacting after they hit aggregator sites or news feeds. Macro awareness for high-timeframe trades Grok AI enables traders to track real-time sentiment around macroeconomic events like CPI releases, interest rate decisions and crypto regulations. For example, following the December 2024 US Consumer Price Index (CPI) report, which showed an annual inflation rate of 2.9%, Bitcoin briefly crossed $98,500. This movement aligned with market expectations and was interpreted by some analysts as a bullish signal for risk assets, reflecting optimism about potential Federal Reserve rate cuts. By parsing crowd-level data in real time, Grok often provides a clearer picture of market positioning than traditional headlines. This insight can help traders time capital rotations between BTC, stablecoins or altcoins more effectively, especially when market sentiment shifts rapidly post-macro events. Grok vs. ChatGPT for crypto trading Grok and ChatGPT are both AI tools being explored for crypto analysis, but they serve different functions. For traders, analysts or researchers looking to improve decision-making, understanding where each tool fits can help streamline different parts of the workflow. Grok is integrated with X and is available to X Premium+ users. Its key strength is real-time sentiment parsing. It can track public posts, monitor trending discussions, and flag early signals based on community chatter. This makes it useful for identifying potential momentum shifts tied to market narratives, token mentions or macroeconomic events. ChatGPT, on the other hand, is more effective for structured analysis. It doesn't access live social feeds unless connected to APIs or plugins. However, it can explain trading strategies, summarize research and interpret technical indicators based on user inputs. This makes it suitable for backtesting concepts, understanding token mechanics or generating trade logic for bots. Developers in AI trading communities often pair both tools — using Grok to identify emerging trends from real-time sentiment and ChatGPT to refine strategies, simulate scenarios, or build automation logic around those signals. Data access: Real-time vs. processed knowledge Grok has a major advantage when it comes to real-time information. Because it's embedded directly into X, Grok can scan live posts, community reactions and trending content as it happens. That makes it incredibly useful for: Capturing sudden sentiment shifts Spotting viral token mentions before price moves Reacting to breaking macro or regulatory news. ChatGPT, on the other hand, doesn't have live feed access unless you connect it to external tools (like a browser plugin or API). Its strength lies in structured analysis, explaining trading strategies, running conceptual backtests or summarizing white papers. If you need fast input from the crypto crowd, Grok wins. If you need structured insight or technical breakdowns, ChatGPT is your tool. Sentiment vs. strategy Grok is particularly effective at analyzing real-time social narratives across crypto communities. It's ideal for: Crypto sentiment from X Identifying early crypto signals from trending posts and community chatter Identifying memecoin rotations and community-driven pumps Gauging macro reaction in real time. ChatGPT is more effective for: Writing or debugging trading bots Explaining concepts like liquidation cascades or funding rates Developing AI-powered crypto trading strategies. For example, the AI4Crypto GitHub repo includes scripts integrating Grok sentiment with backtesting logic via ChatGPT. These experimental setups are becoming more common in open-source quant groups, while ChatGPT is used to draft trading logic or simulate responses. These paired setups are becoming more common in open-source quant groups and AI-based trading experiments. Speed of deployment Grok is designed to be reactive. It detects signals the moment they start trending. This has led developers in the crypto automation space to experiment with building auto-trading alerts that respond to Grok-identified sentiment spikes. ChatGPT, by contrast, requires more setup. Unless integrated with real-time APIs, it works best with questions grounded in historical or static data. That's not a flaw — it's intentional. Grok acts as a market listener; ChatGPT functions as a strategy explainer. Risks, limitations and what Grok can't do for crypto traders As promising as Grok is, it's important to understand its boundaries. Traders experimenting with AI often run into issues not because the tool is bad, but because they expect it to do everything. Grok can enhance your workflow, but it's not a plug-and-play magic signal generator. No trade execution logic Unlike a crypto bot connected to an exchange, Grok doesn't execute trades or manage positions. It can alert you to rising sentiment or narrative shifts, but it won't know whether your strategy is risk-on or risk-off. Some traders are building Grok-connected scripts for trade alerts, but these setups still require manual review or pairing with third-party execution platforms. Bottom line: Grok is a signal scout, not a full-stack trading engine. No charting or technical indicator awareness Grok 3 has introduced early-stage support for parsing some market data and basic chart patterns, but it still lacks full technical analysis (TA) capabilities. For precise TA, traders should still rely on tools like TradingView or dedicated bots. That's a major difference from tools like ChatGPT, which can explain and simulate trading strategies using TA logic. So, while Grok might tell you, 'SHIBA is trending,' it won't say, 'This is a bullish flag on the 4H.' For that, you'll still need TradingView, CoinGlass or a hybrid AI setup. Susceptible to noise and manipulation Because Grok pulls directly from X, it's reading unfiltered public data, which can include misinformation, coordinated shilling or sentiment spoofing. During memecoin cycles, it's common for groups to artificially inflate mentions, hype or fake news. If Grok is used without filtering or human context, it might flag these as bullish signals when they're just exit liquidity traps. This is one of the biggest risks of trading with Grok AI: You're relying on the crowd's words, not the market's confirmations. Limited depth on altcoins While Grok is strong at identifying trending topics, it struggles when sentiment data is thin. For smaller altcoins with low visibility or limited community discussion, Grok may return weak or irrelevant signals. Traders using Grok for niche decentralized finance (DeFi) or microcap tokens may get better results by pairing it with crypto technical analysis software or onchain tools like Nansen. No built-in risk management Grok doesn't know your portfolio size, stop-loss level or risk tolerance. It won't warn you that you're overexposed, chasing pumps or trading against a trend. This is where most new traders overestimate AI. AI-powered crypto trading strategies still require a human layer of risk control. Grok might tell you what's hot, but it's your job to decide if it's worth chasing. Source:


Khaleej Times
9 hours ago
- Khaleej Times
'Stopped using my brain': UAE residents hit by ChatGPT outage reveals AI dependence
When ChatGPT went dark on Tuesday, some UAE residents found themselves unexpectedly stuck, unable to draft emails, write code, compile assignments, or finish work reports. The global outage of the popular AI tool sparked widespread confusion and frustration, especially among those who have come to rely on it for everyday tasks. Experts say the disruption serves as a reminder of how deeply generative AI is now embedded in the daily lives of people across the Emirates, and the vulnerabilities that come with that dependence. At exactly 3.40pm, Nadia M., a 25-year-old employee at a marketing agency in Dubai, needed to send a reply to an important email. As usual, she turned to ChatGPT. She pasted the email she had received and typed in a simple prompt in her simple way: 'Make it professional.' Instead of getting a response, she was met with an 'error message stream.' She refreshed the page once, then again, and even tried using her phone. Nothing worked. 'I know I can write this email by myself, it wouldn't take me more than two minutes,' Nadia confessed . 'But I can't put my finger on it... was it full reliance on ChatGPT or just a lack of confidence in myself?' What happened? Users in the UAE were among the thousands worldwide impacted by Tuesday's OpenAI outage, according to Downdetector, a website that tracks digital service disruptions. Globally, around 93 per cent of users reported issues while using ChatGPT, with the rest facing login and app-related problems. Reports peaked around 1.30pm UAE time, with continued disruptions well into the afternoon. In the Emirates, complaints hit a high at 1.40pm. About 60 per cent of UAE users faced website-related issues, 38 per cent had trouble logging in, and a small percentage struggled with the app itself. When Nadia she saw headlines about the global outage, she said she was shocked. 'Those couple of hours made me realise I had actually stopped using my brain,' she said. 'I woke up the next day and continued to use ChatGPT, of course, but I now feel like I need to limit my dependence. Still, it helps me focus more on creativity rather than smaller, routine tasks.' The outage, however, wasn't just a professional inconvenience. For others, it felt oddly personal. 'My emotional support AI was offline,' said Eman, a 27-year-old Dubai resident. 'It was like losing contact with someone real.' She was at work at a café in Umm Suqeim when she noticed the site wasn't responding. 'It didn't make sense to me. I felt weirdly disconnected, and I actually left work early because of it.' 'It felt strange not to get a response from ChatGPT, it's usually so fast and reliable.' Earlier this year, OpenAI simplified the login process by removing the sign-up requirement for new users. Although the service was originally launched only for paid subscribers, it was later rolled out to the public with some limitations for free users. This wider accessibility is expected to challenge traditional search engines like Google and Bing, while also increasing user dependency. Expert view: More demand, more risk Bob Wambach, VP of Portfolio and Strategy at Dynatrace, said the growing reliance on AI tools like ChatGPT brings new risks, especially when it comes to resilience. 'The complexity of the IT systems underpinning public-facing AI services, combined with rapidly increasing interest and user traffic, makes ensuring reliability a challenge,' he said. 'In the case of ChatGPT, users are increasingly reliant on the tool in their personal and professional lives, and any outages will inevitably cause frustration.' Wambach added that AI-powered monitoring will be essential to prevent future disruptions. 'Human capacity simply can't pace and scale at the rate needed to continually monitor, analyse, and optimise software in real-time, only AI can.' AI use in the UAE A recent report by Boston Consulting Group showed that 91 per cent of UAE consumers are aware of generative AI, and 34 per cent are active users. Among students, the figure is even higher: 32 per cent report weekly interaction with such tools. As generative AI continues to shape how people communicate, work, and learn in the UAE, the outage offered a rare and revealing, moment of pause. 'It made me realise I've stopped doing things the hard way,' Nadia said. 'Maybe I need to start again, at least a little.'


Al Etihad
a day ago
- Al Etihad
Meta creating new AI lab to pursue ‘superintelligence'
10 June 2025 23:12 SAN FRANCISCO (THE NEW YORK TIMES NEW SERVICE)Meta is preparing to unveil a new artificial intelligence research lab dedicated to pursuing "superintelligence,' a hypothetical AI system that exceeds the powers of the human brain, as the tech giant jockeys to stay competitive in the technology has tapped Alexandr Wang, 28, the founder and CEO of AI startup Scale AI, to join the new lab, sources said, and has been in talks to invest billions of dollars in his company as part of a deal that would also bring other Scale AI employees to the has reportedly offered seven- to nine-figure compensation packages to dozens of researchers from leading AI companies such as OpenAI and Google, with some agreeing to join, sources new lab is part of a larger reorganisation of Meta's AI Zuckerberg, Meta's CEO, has invested billions of dollars into turning his company, which owns Facebook, Instagram and WhatsApp, into an AI OpenAI released the ChatGPT chatbot in 2022, the tech industry has raced to build increasingly powerful AI. Zuckerberg has pushed his company to incorporate AI across its products, including in its smart glasses and a recently released app, Meta in the race is crucial for Meta, Google, Amazon and Microsoft, with the technology likely to be the future for the industry. The giants have pumped money into startups and their own AI has invested more than $13 billion in OpenAI, while Amazon has plowed $8 billion into AI startup behemoths have also spent billions to hire employees from high-profile startups and license their technology. Last year, Google agreed to pay $3 billion to license technology and hire technologists and executives from a startup that builds chatbots for personal February, Zuckerberg, 41, called AI "potentially one of the most important innovations in history.' He added, "This year is going to set the course for the future.'Meta and Scale AI declined to comment. Bloomberg earlier reported that Wang was joining the new Meta is regarded by leading researchers to be a futuristic goal of AI Google and others have said their immediate aim is to build "artificial general intelligence,' or AGI, shorthand for a machine that can do anything the human brain can do, which is an ambition with no clear path to success. Superintelligence, if it can be developed, would go beyond AGI in its has invested in AI for more than a decade. Zuckerberg created the company's first dedicated AI lab in 2013, after losing out to Google in trying to acquire a seminal startup called DeepMind. DeepMind is now the core of Google's AI then, Meta's research efforts have been overseen by its chief AI scientist, Yann LeCun, who is also a New York University professor. LeCun is a pioneer of neural networks, the technology that drives ChatGPT and similar ChatGPT caused an explosion of interest in AI, Meta deployed additional resources to pursue the technology. One of Meta's strategies for gaining ground in AI has been to "open source' its software, essentially giving away its AI code freely so that developers and others adopt its tools. The company released an open-source AI model, Llama, and its chatbot product, Meta AI was incorporated across Facebook, Instagram and WhatsApp, as well as in its Ray-Ban smart glasses. In May, Zuckerberg said more than 1 billion people used Meta AI every month.