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9 Ways AI is Powering Google Products

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Google AI

The past few years have seen huge breakthroughs in the use and application of artificial intelligence — and AI holds major promise for people around the world.  AI already powers Google’s core products that help billions of people every day.

Here are nine ways we use AI today to make our products even more helpful, including some of our recently announced features:

Search: When Google was founded, most searches happened on computers in homes, computer labs or libraries. Twenty-five years later, AI is making it possible to search in new languages, with new inputs (like searching with your camera or even humming a tune) and even multiple inputs at once. And now, thanks to multisearch, you can search with images and text at the same time with the Google app. So next time you’re inspired by an interesting wallpaper pattern, you can just snap a photo and add text to find that pattern on a shirt. The ability to multisearch is powered by the latest in computer vision and language understanding techniques.

Maps: Google Maps uses AI to analyze data and provide up-to-date information about traffic conditions and delays — sometimes helping you avoid a traffic jam altogether. Now with an immersive view, Google Maps fuses together billions of Street View and aerial images to create a rich, digital model of the world – letting you truly experience a place before you ever step foot inside. With AI, we use 2D images of a venue to generate a highly accurate 3D representation that models the true complexity of what a place is like – so you can see if a restaurant has great lighting for a date night or an awesome outdoor seating area.

Translate: uses AI and machine learning to break down language barriers and allow people to connect across the world. We’re continuing to push state-of-the-art ML-driven translation, now with 133 languages supported. And we’ve expanded the number of languages available on-device in the Translate app as well, with 33 new ones available to use whether you have a network connection or are travelling without one, including Basque, Corsican, Hawaiian, Hmong, Kurdish, Latin, Luxembourgish, Sundanese, Yiddish and Zulu, among others, to make helpful translations more accessible and less network-dependent.

Pixel: AI helps your Pixel phone instantly translate between 21 languages in chat, as well as facilitates a verbal conversation between 6 different languages in Interpreter Mode. It’s also what enables Magic Eraser to remove distractions from photos.

Photos: People take a lot of photos, but an abundance of pics makes it easy for memories to get buried. So back in 2015, we developed AI in Google Photos to help you search for photos by what’s in them. And more recently, we’ve used AI in Photos to help you revisit forgotten “Memories.”

YouTube: YouTube uses AI to automatically generate captions for videos, making them more accessible to a wider audience, including those who are deaf or hard of hearing.

Assistant: Human beings speak like…human beings. For a long time, computers did not. The Natural Language Processing (NLP) AI technology developed for Assistant allows it to understand and respond in a way that mimics human communication — which allows it to parse the text of your question that tries to identify the meaning of your question. So AI is what enables your phone, your Home, your TV, or your car to understand what you mean by “Hey Google, where’s the closest dog park” — and quickly get you directions.

Gmail: We’re all familiar with features like autocomplete and spell check, both of which are powered by AI. But if you’ve ever wondered why Gmail is less spammy than other email services — look to AI. Our spam-filtering capabilities are powered by AI, and they block nearly 10 million spam emails every minute — and prevent more than 99.9% of spam, phishing attempts and malware from reaching you.

Google Arts & Culture’s “Woolaroo” helps 17 global language communities to preserve, expand and share their language with you. By applying machine learning, Woolaroo can recognize objects in front of your camera and propose translations for them – promoting language learning and preservation of heritage, including Mãori, Louisiana Creole and Yiddish.

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5 Ways AI is Transforming Consumer Intelligence and Analytics

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AI consumer analytics

The rules have changed. How companies actually know their customers — really know them — looks almost nothing like it did ten years ago. Old-school research methods are drowning. Too slow, too narrow, too dependent on humans manually stitching together datasets that have already gone cold. Markets shift in days now, not quarters. And the cost of a slow read on consumer behavior keeps climbing. This isn’t just a tooling upgrade. The underlying logic of how businesses decide what to build, what to charge, and who to reach has been gutted and rebuilt from scratch. Staying reactive isn’t a strategy anymore. It’s a liability.

1. Real-Time Data Processing and Pattern Recognition

Consumer intelligence used to run on stale numbers. Analysts dug into data weeks — sometimes months — after whatever actually happened. Modern AI kills that lag. Entirely. These systems chew through enormous volumes of behavioral data on the fly, surfacing patterns that human teams couldn’t find in the same timeframe with ten times the headcount. Machine learning algorithms can process millions of customer interactions, transactions, and behavioral signals simultaneously — pulling clean signal out of what would otherwise be undifferentiated noise. A retailer can track sentiment across social media, reviews, and support tickets right now, catching a brewing problem or an emerging trend in hours rather than weeks. Inventory shifts, pricing moves, message pivots — all of it happens before a trend fully crystallizes. That’s a different game entirely.

2. Predictive Analytics and Consumer Behavior Forecasting

Here’s what actually changed: AI stops consumer intelligence from being a backward-looking exercise. Instead of cataloguing what customers already did, companies can now forecast what they’re likely to do next — and with striking accuracy. Advanced ML models thread together historical patterns and live behavioral signals to predict churn, flag high-value prospects, and project demand across entire product lines. A telecom company can spot which customers are quietly drifting toward a competitor before they ever make the switch — and intervene first. That’s not a marginal improvement. It’s a fundamentally different posture. Resources flow toward the segments that actually matter, rather than spreading thin across the whole base and hoping something sticks.

3. Personalization at Scale

Consumers expect personalized experiences. Full stop. Meeting that expectation at scale — for millions of people at once — is simply beyond what human analysts and traditional segmentation can deliver. Machine learning models read individual purchase histories, browsing patterns, preferences, and demographic signals to build dynamic profiles that drive product recommendations, custom messaging, and tailored interfaces. When building and refining these individualized profiles, marketers who need to enrich their first-party data with verified behavioral signals rely on audience data providers to ensure their models are trained on accurate, high-quality consumer information. An e-commerce platform can serve each visitor a genuinely different experience — different layouts, different offers, different content — all built around that visitor’s unique fingerprint. Conversion lifts. Lifetime value climbs. People respond when recommendations actually fit their lives, not just the average of everyone else’s.

4. Sentiment Analysis and Brand Perception Monitoring

Knowing how consumers feel about a brand means wading through unstructured mess. Reviews, comment threads, support tickets, social posts, video captions — none of it parses cleanly by hand at any useful speed. Natural language processing handles it. NLP systems automatically scan text-based content across digital channels, classifying sentiment as positive, negative, or neutral while bucketing feedback by topic, product feature, or customer segment. An automaker can track online conversations about a specific reliability concern and catch it before it snowballs into a full-blown reputation crisis. No waiting for quarterly surveys. No lag. Brand perception monitoring becomes continuous — and decisions about product fixes, messaging shifts, or service interventions get grounded in real signal rather than gut instinct.

5. Competitive Intelligence and Market Positioning Analysis

Competitive intelligence used to mean manual tracking, sprawling spreadsheets, and perpetually incomplete pictures. AI automates the entire collection-and-analysis loop. ML models watch competitor pricing moves, product launches, promotions, and messaging shifts across digital channels — then stack that data against a company’s own position. Gaps surface. Threats register earlier. A financial services firm can monitor exactly which themes competitors are pushing on social media and which ones are actually generating engagement — then sharpen their own positioning accordingly. Real-time visibility into competitive dynamics means strategic calls about where to invest, which markets to enter, and how to stand apart in crowded categories aren’t made blind anymore.

Conclusion

What AI has done to consumer intelligence isn’t incremental. It’s structural. Real-time processing of massive datasets. Forecasting future behavior instead of autopsying the past. Personalization that reaches millions, not hundreds. Continuous sentiment monitoring. Automated competitive tracking. None of these were realistic options a decade ago. They are now. Companies that wire these capabilities into their core operations make faster, sharper decisions — ones that show up directly in revenue, satisfaction scores, and market share. Those that don’t will keep falling further behind. And the gap between organizations that wield these tools well and those still grinding through traditional approaches? It’s not closing. It’s widening every quarter.

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Redtech Broadens West African Presence, Earns Global Fintech Recognition

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Redtech

By Adedapo Adesanya

Redtech, a financial technology company backed by Mr Tony Elumelu’s Heirs Holdings, has intensified its pan-African expansion strategy as it extends its payment infrastructure beyond Nigeria and leverages recent global recognition to strengthen its footprint across the continent.

The fintech firm was named in the payments category of the World’s Top Fintech Companies 2026 ranking by CNBC and Statista. It is among the only 11 African companies recognised in this year’s edition.

Developed by CNBC and Statista, the annual ranking identifies 500 leading fintech companies from a pool of more than 3,500 businesses worldwide. Serving as a data-driven benchmark, the ranking highlights companies shaping the future of financial services through technology, innovation and scalable digital solutions.

The company said it is accelerating its push into new African markets with the rollout of digital banking and payment solutions.

As part of this expansion, the UBA RedPay mobile application is now operational in Benin, Burkina Faso, Côte d’Ivoire, Mali and Senegal, marking the company’s first significant digital banking presence outside Nigeria.

It has also introduced virtual account services in Ghana through a partnership with UBA, broadening its payment collection capabilities in West Africa.

The company said the move aligns with its long-term ambition to build a unified payment infrastructure that enables businesses to collect, process, reconcile, disburse and manage funds seamlessly across African markets.

Commenting on the company’s growth strategy, the chief executive of Redtech, Mr Emmanuel Ojo, said Africa’s increasingly interconnected digital economy requires payment infrastructure that can support cross-border commerce.

“Recognition from CNBC and Statista reflects the growing relevance of African Fintech companies on the global stage and validates our ambition to build Redtech into Africa’s payment infrastructure company.

“We are building the technology that enables businesses of every size to collect, pay and manage money seamlessly across channels and markets. As African commerce becomes increasingly digitally connected across multiple market borders, businesses need payment infrastructure that is reliable, secure, interoperable and designed for the realities of operating across the continent.

“Our goal is to help power that growth by making payments simpler and more connected for African businesses, while building solutions that reflect global standards.”

Redtech continues to scale its operations, with available numbers showing that the fintech has processed approximately N45.84 trillion ($33.21 billion) in transaction value through its flagship RedPay platform and deployed more than 55,000 point-of-sale terminals serving merchants across sectors including banking, fintech, retail, hospitality, energy and utilities.

Looking ahead, the company said it plans to expand its collections and financial infrastructure capabilities across all 54 African countries, enabling businesses and financial institutions to manage transactions across multiple markets through a single technology platform.

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CREDICORP Expands Consumer Credit for Locally-assembled Digital Devices With C.L.I.C.K.D.

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C.L.I.C.K.D. scheme

By Modupe Gbadeyanka

To expand affordable consumer credit for locally assembled laptops and devices for digital workers, the Nigerian Consumer Credit Corporation (CREDICORP) has launched the C.L.I.C.K.D (Credit for Laptops, Internet, Connectivity and Knowledge Digital Devices) scheme.

This initiative is in partnership with the federal government through the Three Million Technical Talent (3MTT) Programme.

It was designed to democratise access to consumer credit, expand economic opportunity and empower millions of Nigerians to improve their quality of life through responsible borrowing.

At the unveiling of the scheme on Tuesday in Abuja at the Afreximbank African Trade Centre (AATC), the chief executive of CREDICORP, Mr Uzoma Nwagba, said the initiative focuses on fellows’ training through the Learn2Earn platform, many of whom are acquiring in-demand digital skills without access to the devices needed to complete their training and transition into employment or entrepreneurship.

Delivered in collaboration with Fidelity Bank as credit administration partner and NASENI and Imose Technologies as device manufacturers, it will provide 1,000 locally assembled laptops to eligible fellows across Nigeria, with 77 beneficiaries in Abuja receiving their devices at the launch ceremony as the first phase of a nationwide rollout.

Assembling the devices in Nigeria shows how consumer credit can expand digital inclusion, strengthen local manufacturing and deepen the country’s technology ecosystem.

“C.L.I.C.K.D. transforms digital devices from a barrier into an opportunity. By embedding affordable consumer credit into a national talent programme like 3MTT, starting with locally assembled laptops, we are giving qualifying Nigerians a responsible pathway to the tools they need to learn, work and earn, while advancing the federal government’s vision for industrial development and job creation on both sides,” Mr Nwagba averred.

Also commenting, the Minister of Communications, Innovation and Digital Economy, Mr Bosun Tijani, said, “Nigeria’s digital economy can only thrive when our people have both the skills and the tools to succeed.

“Through C.L.I.C.K.D., we are helping qualifying Nigerians participate more fully in the opportunities created by the 3MTT initiative while strengthening local manufacturing through the use of locally assembled devices.”

C.L.I.C.K.D. is CREDICORP’s flagship device financing initiative, open to working Nigerians nationwide, with the 3MTT programme as launch partner for this first phase. Interested Nigerians can register at www.credicorp.ng/clickd.

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