Canva AI Tools Freelancers Can Use To Streamline Their Business
A focused young woman with curly hair, dressed in a yellow shirt, working intently on a laptop in a ... More brightly lit home office setting.
Canva continues to innovate and push the boundaries of what is possible as an online design studio. In April 2025, Canva unveiled "Visual Suite 2.0" - a slew of updates and features that push it past its creative content origins and into a full AI technology suite.
Particular tools could change the game for freelancers who constantly navigate tight budgets, limited time, and multiple clients. This article will explore some of Canva's best AI tools and how they can help streamline freelancers' marketing and business admin.
Not a fan of Excel spreadsheets? You are in luck. No more time wasted trying to figure out formulas. Canva Sheets makes spreadsheets more straightforward, user-friendly, and design-led, perfect for time-stretched freelancers.
Whether you need to present data such as a monthly report, create a content calendar, present project timelines, or even house your own business accounts, Canva Sheets brings it all together in one platform. You can utilize existing templates or create a new one with the help of AI and use drag-and-drop components to suit your business needs. You can even import data or other existing information from Google Analytics, Microsoft Excel, and HubSpot.
Within Canva Sheets is the AI-powered 'Magic Insights', which you can use for data analysis and trend spotting. When used together, you can present data and insights to your clients or stakeholders that are visually-appealing and consistently on-brand with your other marketing collateral.
Data visualization is now accessible to everyone - even freelancers who have no experience in the sort. You can instantly turn your data into easy-to-digest and on-brand visualizations like pie charts, line graphs, and bar graphs. This tool can even suggest the best type of visualization for your data.
Ready to convert your data from Canva Sheets into an eye-catching document that is easy for clients to understand? You can incorporate your newly made charts and graphs into a visually beautiful and on-brand document, such as an infographic or slide deck. Visual communication is essential for data-driven storytelling in business, so this tool is helpful for freelancers who don't count graphic design as a strength yet need to create documents that make an impact.
Within Canva's Magic Studio are a wide variety of AI tools - such as Magic Resize to reformat documents, Magic Edit for photo editing, and Magic Animate to add motion to your designs. These can all help bring your imagery, videos, documents, case studies, digital products, and proposals to life, saving you hours of precious time.
Finally, one of Canva's newest tools is Canva Code. It's an AI-powered solution for freelancers juggling design and development within their business and for those with little to no coding experience (which is many of us!). Canva Code makes it easier for freelancers to create a landing page, website, online portfolio, email templates, or even interactive tools like quizzes and calculators in less time than on traditional or separate platforms.
In a digital world where speed, automation, and visual impact matter more than ever before, Canva offers freelancers a comprehensive range of AI tools. Whether you're creating reports, data visualizations, documents, or marketing materials, for yourself or your clients, Canva's AI tools empower freelancers to make strategic business moves through a more automated and streamlined workload.
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Fast Company
44 minutes ago
- Fast Company
The real data revolution hasn't happened yet
The Gartner Hype Cycle is a valuable framework for understanding where an emerging technology stands on its journey into the mainstream. It helps chart public perception, from the 'Peak of Inflated Expectations' through the 'Trough of Disillusionment,' and eventually up the 'Slope of Enlightenment' toward the 'Plateau of Productivity.' In 2015, Gartner removed big data from the Hype Cycle. Analyst Betsy Burton explained that it was no longer considered an 'emerging technology' and 'has become prevalent in our lives.' She's right. In hindsight, it's remarkable how quickly enterprises recognized the value of their data and learned to use it for their business advantage. Big data moved from novelty to necessity at an impressive pace. Yet in some ways, I disagree with Gartner. Adoption has been widespread, but effectiveness is another matter. Do most enterprises truly have the tools and infrastructure to make the most of the data they hold? I don't believe they do. Which is why I also don't believe the true big data revolution has happened yet. But it's coming. Dissecting the Stack A key reason big data is seen as mature, even mundane, is that people often confuse software progress with overall readiness. The reality is more nuanced. Yes, the software is strong. We have robust platforms for managing, querying, and analyzing massive datasets. Many enterprises have assembled entire software stacks that work well. But that software still needs hardware to run on. And here lies the bottleneck. Most data-intensive workloads still rely on traditional central processing units (CPUs)—the same processors used for general IT tasks. This creates challenges. CPUs are expensive, energy hungry, and not particularly well suited to parallel processing. When a query needs to run across terabytes or even petabytes of data, engineers often divide the work into smaller tasks and process them sequentially. This method is inefficient and time-consuming. It also ends up requiring more total computation than a single large job would. Even though CPUs can run at high clock speeds, they simply don't have enough cores to efficiently handle complex queries at scale. As a result, hardware has limited the potential of big data. But now, that's starting to change with the rise of accelerated computing. Breaking the Bottleneck Accelerated computing refers to running workloads on specialized hardware designed to outperform CPUs. This could mean field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs) built for a specific task. More relevant to big data, though, are graphics processing units (GPUs). GPUs contain thousands of cores and are ideal for tasks that benefit from parallel processing. They can dramatically speed up large-scale data operations. Interestingly, GPU computing and big data emerged around the same time. Nvidia launched CUDA (compute unified device architecture) in 2006, enabling general-purpose computing on graphics hardware. Just two years earlier, Google's MapReduce paper laid the foundation for modern big data processing. Despite this parallel emergence, GPUs haven't become a standard part of enterprise data infrastructure. That's due to a mix of factors. For one, cloud-based access to GPUs was limited until relatively recently. When I started building GPU-accelerated software, SoftLayer—now absorbed into IBM Cloud—was the only real option. There was also a perception problem. Many believed GPU development was too complex and costly to justify, especially for general business needs. And for a long time, few ready-made tools existed to make it easier. Those barriers have largely fallen. Today, a rich ecosystem of software exists to support GPU-accelerated computing. CUDA tools have matured, benefiting from nearly two decades of continuous development. And renting a top-tier GPU, like Nvidia's A100, now costs as little as $1 per hour. With affordable access and a better software stack, we're finally seeing the pieces fall into place. The Real Big Data Revolution What's coming next will be transformative. Until now, most enterprises have been constrained by hardware limits. With GPU acceleration more accessible and a mature ecosystem of supporting tools, those constraints are finally lifting. The impact will vary by organization. But broadly, companies will gain the ability to run complex data operations across massive datasets, without needing to worry about processing time or cost. With faster, cheaper insights, businesses can make better decisions and act more quickly. The value of data will shift from how much is collected to how quickly it can be used. Accelerated computing will also enable experimentation. Freed from concerns about query latency or resource drain, enterprises can explore how their data might power generative AI, smarter applications, or entirely new user experiences. Gartner took big data off the Hype Cycle because it no longer seemed revolutionary. Accelerated computing is about to make it revolutionary again.
Business of Fashion
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Influencers and LGBTQ+ activists have rolled their eyes at corporate Pride celebrations for years, viewing these efforts as rainbow-washing — latching onto the cause mostly for its marketing potential — or just plain tacky. But the subdued tenor to 2025 Pride merch comes as many brands are avoiding public engagement with progressive causes amid a backlash by right-wing activists and the Trump administration, which has shaken the private sector by declaring DEI efforts unlawful and threatening to release a list of 'woke companies.' In one survey by Gravity Research, a risk management firm, 39 percent of corporate leaders said they planned to reduce 2025 Pride activities, with 61 percent citing fear of retaliation from Trump as a reason. LGBTQ+ youth nonprofit The Trevor Project 'has seen a dip in support from corporate partners this year,' said a spokesperson, and many cities' Pride parade organisers report a steep drop in sponsorships. 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Some mainstream brands' collections evoke pop stars more than politics this year. Brands used to 'approach Pride with a sense of humour,' said Clary, who noted that Target's cringiest catchphrase merch has disappeared since 2023, when an uproar about trans-friendly swimsuits resulted in violent threats to employees and the retailer pulled items from stores. There are still some whimsical touches at Target, including a rainbow mesh dress and a 'Love is for all' slogan T-shirt. A miniature moving truck featuring bird figurines and the lesbian flag colours has gone viral. In a statement, Target said it 'will continue to mark' Pride month with products, internal programming and event sponsorships. 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(Screenshots) Standing Up Not all labels are shying away from rainbows or provocation this year, as shown by a bright watch capsule by Guess and a lascivious Diesel collection and campaign cast from the social networking app Grindr. Whether bland or bold, most brands' Pride items are combined with donations to LGBTQ+ causes. Pride is a crucial fundraising month for advocacy, but takes on more urgency this year amid what a Trevor Project representative called 'uniquely challenging political environment' in the US. Abercrombie & Fitch, Lululemon, Sephora, MAC Cosmetics and Rare Beauty are among The Trevor Project's continued supporters. Levi's 2025 collection doesn't have anything as bold as the purple gender-neutral dress by a non-binary textile artist it offered for Pride in 2023. But it was designed in collaboration with the GLBT Historical Society, and the company is one of a small number of large brands to publicly stand by its DEI efforts. 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Kim Petras poses with MAC Cosmetics' special-edition lip gloss for Pride 2025. (MAC Cosmetics) Pairing Pride marketing and merchandise with donations helps brands counter accusations of rainbow-washing. Experts also highlight the importance of continuing to elevate the work of smaller artists in the community, especially in the face of right-wing backlash. Not all brands have given in to their own customers' blowback. Nascar has eschewed critics of its kitschy rainbow Pride shirts with phrases like 'Slaytona.' One with 'Yaaascar' in rainbow letters was among the only Pride items that Clary has accepted as a PR gift. 'The move is to crop it and then wear it,' said Clary.
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Trafigura Warns of Trading Headwinds as Payouts Outstrip Profits
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