AI took the world by storm. Just like the Industrial Revolution and the advent of the internet, AI also sparked various controversies regarding concerns about job displacement, privacy, security, and ethical implications. Initially, it was rumored that AI would take over jobs, leaving people without a livelihood.
But now, the perspective has somewhat changed. AI doesn’t have the potential of a human mind, and it can never achieve the creativity of one, either. But what it most certainly can do is help humans generate, manage, and organize content in bulk.
The topic of today’s post is AI in Brand asset management. So, let’s get started.
What is Meant by AI in the Context of Brand Asset Management?
Before we move any further, let’s take our time to revise some basic concepts.
Brand Asset management refers to creating, organizing, and distributing branding assets across various platforms and practitioners. The practice is held to uphold consistency in branding, fostering credibility, authenticity, and trust. But as your business grows, so does the number of your branding assets.
Now, you can no longer use the same logo to represent you across various multimedia and digital media content. So you create different trademarks and distinct versions so those trademarks look presentable over different backgrounds and platforms. And the number of these trademarks just goes on increasing and increasing.
Most small businesses start their branding asset management with PDF files. However, they soon realize the process of distributing these files to all stakeholders and team members involved for the slightest change is not only time-consuming but also inefficient. So, they turn to a brand asset management platform, where they can organize and locate all branding assets in one centralized place. The tiniest reforms are notified to every team member. Everyone is on the same page and updated and now works more efficiently towards achieving a strong brand voice.
But even with a BAM platform, the organizing can soon turn into chaos. The tags you initially created for organizing assets may not be relevant anymore. Additionally, your team members might have to surf over the plethora of assets to find the one they’re looking for.
To tackle this problem, we now have AI. Generally speaking, AI enables machines to simulate human intelligence processes, including learning, reasoning, and problem-solving. But with BAM, AI is confined to how brands handle their digital assets by using tools such as machine learning, natural language processing (NLP), and automation.
We won’t lodge you with unnecessary details about these tools, but we will inform you how AI, in itself, can be beneficial for your business. So, let’s skip to that part now.
What are the Perks of Having AI Integrated into your Brand Asset Management Platform?
AI is phenomenal at organizing things and saving time while doing so. Additionally, it is also effective. Here are some critical perks of having AI integrated into your brand asset management platform.
Improved Efficiency and Automation:
Doing the same task repeatedly, day after day, can become frustrating. Moreover, it’s time-consuming. With AI, you can have all the repeated tasks automated, such as informing all stakeholders about the updates regarding branding guidelines or assets. AI algorithms can also automatically tag and categorize images, logos, and other media assets based on predefined criteria. This not only saves time but also reduces human error.
In addition, automation tools can streamline processes like file format conversion, asset resizing, and even content optimization for different platforms. This leads to better productivity and higher job satisfaction as team members can shift their focus to more innovative or complex responsibilities.
Enhanced Consistency and Brand Control:
Consistency is the most important thing in branding. People don’t want to see two sides of the same thing. If your brand is XYZ, represent it as XYZ across all platforms. If your color palette is baby pink and white, be consistent with it across all platforms. But, as your business grows, upholding this consistency becomes increasingly challenging.
AI can help in this regard by monitoring and enforcing brand guidelines across all assets. These artificial intelligence systems can flag deviations from brand standards, such as incorrect logos, unauthorized fonts, or improper color schemes before they are distributed. For instance, machine learning models trained on brand guidelines can instantly identify assets that don’t align with the approved style.
Data-Driven Insights and Predictive Analysis:
One of AI’s most valuable capabilities is its ability to analyze user engagement data to provide actionable insights. Through AI-powered analytics, brands can assess which assets perform best across various platforms.
Then, from these insights, you can optimize future content strategies and adjust your asset creation to align with audience interests. Not only that, but predictive analysis can even anticipate future trends. With those insights, your brand will be the first initiative of the trend. You’ll be innovative and relevant to your industry and your audience, and in turn, you’ll gain a lot of recognition and brand credibility.
Streamlined Collaboration and Accessibility:
In a physical office space, you can easily roll around your chair and go to the supervisor if you have trouble locating a specific asset. But with a remote setup, you can’t do that. AI won’t help you communicate with your supervisor like the physical workspace, either, but it will surely help you locate specific assets with just a prompt.
Additionally, with centralized, cloud-based AI asset management systems, employees can access, edit, and distribute assets as needed, regardless of location.
How to Implement AI Effectively Across Your Brand Asset Management Platform?
At the end of the day, AI is just another technology, and you have to know specific tips and tricks to implement it effectively for optimal functionality and adaptability. Here are some best practices to implement AI effectively in your Brand Asset Management platform.
Start Small and Scale Gradually:
You don’t have to conquer the world tomorrow. You must start low with things at first and get yourself aware of the perks and disadvantages. With AI, the thing is that its integration can get complex at times. So, by starting with small, specific projects, you can build understanding and prove values before fully committing.
Begin with simple tasks, such as automating image tagging or categorizing a subset of assets. This will allow you to learn and adapt. Then, as you become aware of the potentials and setbacks of the technology, expand AI’s role gradually by adding complex processes, like predictive analytics or brand consistency monitoring.
Uphold Data Accuracy and Cleanliness:
AI relies heavily on data, and that is its biggest weakness. The technology focuses on accurate results driven by clean, accurate data. As such, if there are any faults in the data, you won’t get any meaningful results. Instead, you’ll just get a cluster of inefficient results, leaving more work on your table.
But that can be prevented with a simple audit. Before you ask AI to do its job, ensure the data is clean, dated, and accurate. Conduct routine data cleaning and validation to remove duplicates, correct inaccuracies, and update outdated information. This simple routine audit will ensure that the AI algorithms produce more reliable insights and recommendations.
Customize AI Solutions to Fit Brand Needs:
Every brand has its unique values, guidelines, and requirements. A one-size-fits-all approach isn’t the solution for all brands. An AI that may offer this will drive generic results badly, impacting your brand.
Train the AI algorithm to align specifically with your brand’s objectives, asset types, and management needs. For example, a brand focused on visual consistency may prioritize AI for logo recognition, while a content-driven brand might need NLP tools for text-based assets.
Regularly Monitor and Update AI Systems
AI is still in the early stages of its development, and it may take some time before it reaches its full potential. Though some argue that it will never happen, it is still clear as a day that regular updates with this new technology are common. The data updates are one thing, and it’ll drive the AI to stay relevant and effective with its results.
On the other hand, technological advancements are constantly evolving, and these advancements often lead to new AI capabilities, optimizations, and security enhancements. To keep up with these changes, monitor and update your AI systems to ensure they remain effective, secure, and capable of meeting your evolving business needs.
Cherry on Top
After everything, AI is still a tool. It lacks the creativity of a human mind, and as the brains behind the operation, you have to use AI to assist you with Brand Asset Management (BAM) rather than relying on it entirely. Furthermore, if you want to integrate AI into your existing brand asset management platform, the process might be backed up with heavy bills from programmers, and it may still have certain drawbacks.
To address these issues, Ethos offers a centralized brand asset management platform with seamless AI integration. The platform handles all updates related to AI technological advancements, allowing you to focus on leveraging its features to their fullest potential.
There’s never been a better time to try out such an innovative platform with a 30-day completely free trial—no credit card required!
