You’ve probably heard on the news that AI is coming for your job. Is this claim just media-fueled hype or is there evidence to back it up?
According to the World Economic Forum’s Future of Jobs Report 2023, employers estimate that 44% of worker’s skills will be disrupted within the next five years. AI is one of the leading drivers of this shift in workplace skills, and 42% of companies plan to prioritize AI and big data in company skills training. Clearly, AI is going to have a significant impact on the workplace, so what does that mean for your job?
Here’s the good news: companies surveyed in the same report state that analytical thinking and creative thinking still remain the most important core skills for workers, so even though 75% of companies plan to adopt AI and other big data technologies in the next five years, human ingenuity is still the main key to success.
When it comes to digital asset management, AI has proven to be an effective tool for automating many of the tedious manual tasks that slow down project workflows. Creatives, marketers, and other teams that use AI for DAM are seeing greater productivity, as it allows them to shift their energy toward higher-value tasks. This article will take a deep dive into AI for DAM and how you can use it to revolutionize your content ops.
What is AI Digital Asset Management?
Digital asset management requires users to perform many tedious tasks, like:
- Creating detailed descriptions of visual assets
- Metadata tagging and asset categorization
- Searching for desired assets that may be hidden due to incorrect classification or are deep in layers of subfolders
- Converting files into different formats and cropping them into different sizes
- Re-working existing content to suit new use cases
- Making sure assets follow brand guidelines
- Identifying and fixing compliance issues
Many of these tasks are time consuming and don’t require much creativity. This means that marketing, digital experience, and content and creative teams are using a lot of resources to handle tasks that could be more efficiently completed by AI.
AI is revolutionizing DAM by accelerating content creation, automating asset management, and making it quick and easy to find the assets you need.
Ultimately, though, AI won’t improve bad processes. Before you simply assign automation to tasks in your traditional workflows, think about how intelligent asset management can allow you to reorganize your existing structures for greater productivity and workplace efficiency.
This means:
- Forging partnerships between humans and AI tools that enhance value creation rather than dividing tasks into ‘creative’ or ‘automatable’ categories
- Investing in technology that empowers people to dedicate more time and energy to higher-value tasks that drive revenue growth
IBM discovered that companies that prioritize these types of “operating model” advancements outperform those that focus more on skills-based improvements 44% of the time.
But that doesn’t mean you need to wait until every section of your organization is ready before implementing AI in smaller ways. Organizations can start by identifying “high-impact quick wins” and using them as a basis for scaling up their AI operations.
Benefits of Using AI in Digital Asset Management
Intelligent DAM uses AI to streamline the tedious tasks listed above. It’s becoming so prevalent in content-related operations that 85% of marketers say that generative AI tools have changed the way they create content.
The primary goals of using AI in DAM come down to achieving these three outcomes:
- Streamlining content operations
- Staying on-brand and compliant
- Increasing marketing ROI
Here are some of the ways you can use AI in DAM systems to supercharge your operational efficiency and target these outcomes.
Accelerate your content creation workflows
Generative AI is capable of turning simple prompts into full-fledged drafts that you can use to get a head start on the content creation process, and it can handle video and audio as well.
- Workflow triggers can be set according to predetermined criteria so that approval, conversion, or publishing workflows are streamlined and directed to the right teams and users.
- AI content coaches can turn your digital assets into blogs, marketing copy, or localized content to suit audiences in different contexts.
- Smart transform features enable you to change backgrounds, alter expressions and remove objects from your images.
- Smart cropping speeds up omnichannel publishing by creating image variants based on different crops or focusing on different focal objects.
Enhance asset findability
One of the most frustrating DAM tasks is locating a missing asset. AI addresses this issue by leveraging powerful machine learning techniques to categorize your asset database so that you can find what you need more easily even with vague search terms.
- Visual search allows users to find similar images instead of using text to describe the image.
- Natural language processing makes it easier to use conversational search terms instead of specific tags and keywords. For example, typing “images of people working out” will show you all brand-related fitness assets without requiring you to remember what campaign they were used for.
- Similar content recommendations use facial recognition and other techniques to find similar models, themes, and objects.
Upgrade your asset organization
Organizational structure is the key to any successful DAM platform, and improving current structures is one of the primary reasons why companies seek out DAM software. AI effortlessly handles many of the time-intensive manual tasks involved with asset management.
- Smart tags generate recommended tags for assets according to company-specific taxonomy. Once you set up the structure, the AI model will learn from your instructions and assign the correct tags.
- Predictive metadata can analyze content and auto-generate metadata for users to review later.
- Automated video and audio summaries make it possible to find the right clips without scanning entire videos or audio transcriptions, greatly speeding up review and editing workflows.
Ensure brand safety and compliance
Many organizations are concerned that AI will threaten their data security due to uncertainties around underlying algorithms and training data. That’s why it’s important to use AI DAM platforms that never use your internal data to train public models. Your organization might also have or eventually adopt rules about when and how AI content can be used. Or you may publish content on a channel that requires disclosing the use of AI. A DAM platform can help you comply with those rules.
- AI content detection will automatically identify AI-generated assets and trigger review workflows so that you never unknowingly publish AI content.
- Smart action reviews help you check for legal issues and mark up assets for editing if any issues are identified.
AI’s Real-World Impact in DAM Applications
It’s clear that companies can use AI internally to optimize their existing processes, but how does that translate into real-world impact? Here are some examples of how AI in DAM systems can bring benefits to a wide range of industries and applications.
- Ecommerce: AI DAM systems automatically tag and categorize products by visual style, color, season, or any number of predefined brand-related identifiers. This allows brands to deliver a more customized experience to their online customers. AI analytics can also be used to identify user trends and behaviors to deliver greater personalization and increase conversions.
- Entertainment: Media companies can improve their content discovery capabilities to increase audience engagement and satisfaction. For example, AI can sort through movies or songs at lightning speed to identify specific scenes or lyrics that users might be searching for, or use this information for content personalization and targeting marketing. AI can also be used to identify copyrighted content and protect sensitive assets.
- Manufacturing: AI-powered DAM systems help manufacturers categorize products and their schematics and specifications to streamline production workflows, improve documentation, and monitor quality control.
- Healthcare: AI in healthcare DAM systems helps organize mountains of patient records and medical imagery. This helps healthcare providers deliver faster diagnostics and reduces the prevalence of human-related categorization errors.
- Financial and Legal Services: These industries process huge amounts of paperwork, from loan applications to insurance claims. Intelligent DAM systems help analyze, categorize, and retrieve desired content much faster than traditional file management systems, reducing the likelihood of human errors in the process.
These are just a few examples of areas where AI in DAM can have enormous impact. But AI’s benefits don’t stop here. Almost any industry can benefit from the efficiency and optimization of AI-powered tools.
5 Things to Consider When Evaluating AI DAM Platforms
It’s easy to get caught up in all the exciting possibilities that AI can bring to your DAM workflows, but it’s important to take a step back and consider how AI will fit into your operating model and bring long-term benefits to your organization.
Ask yourself these questions when evaluating DAM platforms and their AI-integrated features:
- Do you have the capacity to implement AI effectively? AI and automation should lighten the load, not create additional headaches. Consider whether your organization currently has the bandwidth and expertise to implement and manage AI effectively. If it doesn’t, what steps do you need to take to get there?
- What specific business problems do you want to solve by using AI in your DAM operations? Ensure that the DAM system you choose can address these issues and has the capacity to solve other issues that may arise as your organization scales.
- Which AI features are essential for your organization? There’s a long list of available AI tools and capabilities, but they may not all be crucial for your business needs. Determine which features are critical for your operations through discussions with users and stakeholders, then design an implementation plan that works for everyone’s needs.
- What metrics will you use to gauge the effectiveness of your AI implementation plan? Determine the metrics you’ll use to gauge potential ROI before integrating AI within your workflows, not just as an afterthought. This will help you keep an eye on long-term objectives and success instead of settling for minor efficiency upgrades.
- What custom AI features do you want to see your organization using in the future? Even if such capabilities aren’t possible at the moment, it can be helpful to imagine a wishlist of features that would have a significant impact for your organization. That way, you can better evaluate if your DAM platform has the potential to fulfill these needs in the future.
Challenges of Using AI in Digital Asset Management
To use AI effectively in DAM, you should be aware of any potential obstacles that could derail your efforts to improve productivity. As mentioned previously, AI won’t solve all of your workflow inefficiencies. It’s just one tool in your arsenal that you can use in combination with others to bring greater value to asset creation and management.
When upgrading your operations to incorporate AI, be aware of these potential issues and consider following these suggestions.
- Challenge: Inaccurate or irrelevant tags can lead to asset misclassification, resulting in DAM system disorganization and making it difficult to find the correct assets.
- Solution: A DAM system’s AI will become more accurate the more you train it on your own content. By using smart tag training and identifying common brand assets, colors, and logos, you can train it to recognize and label things like your company’s products or brand names.
- Challenge: Companies must ensure that their AI systems don’t violate any data privacy laws and are compliant with industry-standard regulations.
- Solution: Only work with DAM providers that adopt enterprise-grade data security standards and have obtained regulatory certification. In terms of AI, your content should be privately secured and never used to train public models.
- Challenge: It can be difficult to convince leadership that automation is one of the keys to successful DAM. Migrating to an intelligent DAM system can also require significant investment and training.
- Solution: Demonstrate the value that automating DAM workflows can have by presenting customer success stories and data from similar companies that have incorporated AI in their digital asset management.
Unleash the Full Potential of Intelligent Digital Asset Management
AI technology is developing at a rapid pace. Today, you might be impressed with its capabilities in content analysis, smart tagging, and workflow automation — but what about the future?
The DAM industry is still in the early stages of AI integration and there are many advancements yet to be discovered. As AI technology evolves and continues to enhance DAM platforms, companies should position themselves to be ready to adopt new features and adjust their operating models.
There isn’t a one-size-fits-all approach to AI integration. You need to be thoughtful about where and how you apply AI in your workflows to generate the most productivity and optimization. Are you ready to learn more about intelligent digital asset management and how it could benefit your organization? Schedule a live, customized demo today and explore the endless possibilities.
