7 Data Capture Trends for 2025

As AI reshapes the tech landscape, how will data capture evolve in 2025? From contextual data capture to diverse barcode formats and hybrid device strategies, here’s seven smart data capture trends to look out for — plus expert insights from analysts and industry leaders.

1. Okay, let’s get AI out the way first

It’s impossible to write a 2025 technology trends blog without referencing AI. But while large language models (LLMs) and GenAI have a place in smart data capture, in 2025 we can expect to see most value in this area being delivered by other forms of AI, particularly computer vision.

The increases in computing power and machine learning capabilities driving breakneck innovation in GenAI are driving similar innovation in computer vision. Not only that, but according to Gartner’s 2024 hype cycle for AI, GenAI will take 2-5 years to reach the plateau of productivity — whereas computer vision is already there.

Shelf intelligence, advanced barcode scanning, and fake ID detection are all areas where AI-powered computer vision is already solving business problems. Expect to hear much more about it in 2025.

2. Data capture will become not only multi-modal but contextual

In 2023, people started talking seriously about multi-modal data capture. This only gathered pace in 2024.

Driven by AI, in 2025 this will go to the next level. We’ll be talking not just about multi-modal but about contextual data capture.

Think, for a minute, of a logistics worker scanning a barcode on an electronics package in a warehouse. Does that barcode exist in isolation? Of course not — it’s printed on a label which also includes text and other barcodes.

Not only that, the printed label is affixed to a three-dimensional package that exists in a physical environment of hundreds of other labels and packages.

In other words, it has context. And the logistics worker isn’t simply interacting with a screen — they’re using their device to capture real-world objects.

Contextual data capture will not only analyze multi-modal data sources (for example, text and barcodes on a label), but understand the wider context and user intent to deliver a more accurate, complete, and useful view of the world.

Multi-modal AI will deliver more context … It allows for more intuitive interactions and significantly improves the accuracy of AI outputs.

Oliver Parker, Vice President, Global Generative AI Go-To-Market, Google Cloud

The enhanced scanning engine in the recent Scandit SDK 7.0 release applies advanced AI algorithms to the device’s camera feed to analyze multiple signals beyond just detecting and decoding barcodes.

By combining these signals, context-based barcode scanning can consistently capture the desired barcode, even when aiming is imperfect or multiple barcodes are in the field of view.

The SDK 7.0 also includes Smart Label Capture — a solution that fully automates label scanning. It uses multi-modal data capture to scan multiple barcodes and printed serial numbers, weights, and expiry dates with just one press.

Smart Label Capture has already saved one US retailer $1.3 million by eliminating data entry errors that were causing them to undercharge customers.

3. It’s a barcode, but not as you know it

Imagine a barcode.

What did you think of? Probably, the collection of vertical black-and-white lines you see every day on product packaging.

Your idea of what a barcode consists of is likely to expand In 2025. We’ll start to see UPC and EAN barcode types being supplemented (or even replaced) by Data Matrix or QR codes on product packaging, as the GS1 Sunrise 2027 initiative gathers pace.

You’ll also see more and more electronic shelf labels (ESLs). These still use UPC or EAN codes, but displayed at a tiny size and without the printed numbers.

There are big benefits to these new barcode styles. Data Matrix and QR codes serve the traditional purposes of product identification and traceability, but can store far more information. Electronic shelf labels allow retailers to make dynamic real-time price updates.

While traditional barcodes suffice for basic tasks, QR codes allow for richer interactions, such as offering promotional discounts or displaying product reviews directly to the customer.

Jess Grisolia, Scandit, in Retail Insight Network

However, more diverse types of barcode will come with challenges. Not all barcodes are equal, and not all barcode scanning software is equal.

Your barcode scanning software might be able to decode a full-size EAN code in good light. But can it reliably scan a tiny barcode on an ESL, a fluorescent postal barcode on an envelope, or a data-dense Aztec code on a train ticket displayed on a passenger’s smartphone screen?

Barcode scanning software in 2025 will need to be able to decode multiple different barcodes accurately and flexibly on a single device. This is another area where advances in AI-powered computer vision will play a big role.

For example, CTT, Portugal’s first and oldest mail provider, recently integrated the ability to scan fluorescent barcodes (previously only scannable on specialist sorting machines) into its last-mile mobility app.

4. Data capture will underpin transparency and trust

Consumers are expected to value transparency even more in 2025. This is especially true for younger generations.

True transparency across the supply chain, corporate social responsibility, pricing, product information, sustainability, and more is what will build brand loyalty in 2025. This in turn depends on being able to connect the physical products consumers buy to digital information. Data capture is what provides that essential connection.

With the free Yuka mobile app, consumers can scan product barcodes and obtain instant evaluations of the nutritional value of food products, or the healthiness of cosmetics ingredients.

Far from being a minor feature, intuitive and friction-free data capture underpins Yuka’s entire value proposition. Smart data capture capabilities are imperative to identify products fast and accurately and match them to database information — one of the reasons that Yuka are an early adopter of context-based barcode scanning.

It’s just one example of how data capture will underpin transparency in 2025.

The grade on the Yuka app is an important factor in consumer purchasing decisions. We have played a crucial part in the industry’s efforts to reduce salt, sugar, and additives in food products. We’re part of the bigger picture.

François Martin, CTO and co-founder of Yuka

5. Flexibility is the name of the game

Although global economic growth is forecast to remain resilient in 2025, there are also significant risks and uncertainty, according to the OECD. In data capture, this will make businesses wary of large-scale automation projects and hardware investments, and push them towards flexible data capture solutions.

Expect to see a greater focus on creating new value and efficiencies from existing hardware investments. New software-first approaches allow businesses to deploy advanced data capture capabilities without upgrading hardware.

Semi-automation that facilitates store associates and customers will also be favoured over full automation. Wearables (such as the Apple Vision Pro, pictured below), smart carts and smart shelves all bring elements of automation without the invasiveness of large hardware projects.

6. Data capture is breaking free from smartphones and handheld computers

In 2025, a new hybrid era is dawning — one where fixed cameras, drones, wearables, and robots work in harmony with smartphones and handheld computers.

Imagine smart cameras monitoring retail shelves 24/7 while store associates’ handheld devices ping them about priority restocks. With smart “co-pilot” systems emerging to combat data overload, businesses can also ensure frontline workers focus on high-impact tasks rather than drowning in alerts.

Businesses will also use this hybrid approach to start small and prove ROI, before scaling up to more ambitious transformations.

Success here won’t just be about collecting data — it’ll be about orchestrating these diverse technologies to work together seamlessly.

7. Data capture will be a weapon in the cybersecurity arms race

And finally, there’s no doubt that in 2025 we will see the technological arms race between enterprises and malicious actors intensifying.

In the world of data capture, the most obvious example of this will be increased adoption of automated identity verification. Manual identity verification will fail to keep up with ever more easily available fake identity documents and stricter data protection and compliance requirements.

In today’s interconnected world, the stakes for robust authentication and proof of identity have never been higher… The surge in data breaches, sophisticated phishing attacks, and the emergence of deepfakes has compounded the urgency for reliable identity verification mechanisms.

Steven Dickens and Keith Kirkpatrick. Futurum

Conclusion: Data capture is becoming a strategic asset

For a long time, data capture was an overlooked capability within IT operations. Now, made smart and revitalized by AI, in 2025 it’s set to become a strategic asset that embeds value creation and resilience at the frontline.

Bridging digital and physical domains is central to any organization’s digital transformation journey. Software-based scanning and advanced data capture solutions represent a valuable conduit, enabling organizations to transform the ubiquitous smartphone and other smart mobile devices with embedded cameras into powerful data capture solutions. This software has evolved considerably and supports capabilities such as continuous and multi-scanning in addition to text, object and image recognition.

VDC Research, 2024