With investors seemingly looking for solutions to digital asset management (DAM), it’s believed that artificial intelligence (AI) can play a role in this context. From an industrial purview, AI-based DAM can help reduce time spent on sorting and categorising assets, and also organise high volume of content.
According to Grand View Research, a market intelligence firm, global AI in asset management market magnitude will grow at a 37.1% compound annual growth rate (CAGR) between 2020-27. MarketsandMarkets, a market researcher, stated that global digital asset management market size should reach eight billion dollars by 2027. “I believe AI can be used to automate processes, detect malicious activities, and provide insights into asset utilisation. AI can also be used to provide digital asset management solutions tailored to needs of the customer,” Vipin Vindal, CEO, Quarks Technosoft, a software company, told FE Blockchain.
Possibilities around AI-based DAM suggest that it can provide cost-effective solutions for managing decentralised finance (DeFi), non-fungible tokens (NFTs), among others. Insights from MerlinOne, an AI-driven platform, mentioned that AI-oriented DAM can provide benefits such as speech-to-text conversion, facial recognition, automatic asset tagging, and visual similarity.
“I think benefits of AI in DAM are that it will decrease cost, save time, enable efficiency, and increase satisfaction. Reportedly, AI can also help reduce human error in tasks such as tagging, categorising, and data entry, leading to data asset management. Another key benefit is that AI can help manage assets by automating processes and workflows, which can make it efficient, reportable, and scalable,” Vikram Goyal, senior director, WNS-Vuram, a hyperautomation services company, stated.
Reportedly, companies such as PixelMill, WebDAM, Bynder, MediaValet, Canto, among others, have been utilising AI-based DAM in their business processes. Moreover, future predictions indicate that AI will contribute towards recognising trends associated with digital assets. As stated by CyanGate, a computer consulting firm, emphasised that AI’s utilisation of data will help DAM and marketing individuals with revenue allocation, through creation of appropriate campaigns.
“The future of AI in digital asset management looks promising, and we can expect to see advancements in this field in the coming years. Furthermore, AI algorithms will handle tasks, from tagging and classifying assets to optimising workflows, resulting in automation. AI-powered analytics tools should provide insights into how users interact with digital assets and how they can be optimised,” Bhaskar Ganguli, director sales and marketing, Mass Software Solutions, a digital transformation company, concluded.