In Parts 1 thru 4 EkaLore looked at an overview of Adobe’s continued overhaul of its products and services by applying Artificial Intelligence (AI) to speed how work gets done. Examples of how these features look at the marketplace in Part 2 were followed by a look at how the marketplace has been changed and will change in Part 3. Part 4 looked at how these new features enable process-level changes at-scale, and for small-medium-enterprises, saving money, speeding up efforts, and setting people up to make decisions. Part 5 looks at a level deeper: what enterprises (small to colossal) will act on to save money, gain process speed, and add functions not previously practical. Part 6 is a perspective of what Adobe invading their own market will mean across functions and industries.
Adobe's success has to be with the success of its business partners, believers, and business-level gains.
Adobe’s increased application of AI to its products and services is subtle and broad. Updates and upgrades see incremental improvements in user interfaces, extending functions to search and discover content, and integration of generative AI for images. Also present, though not discussed at length in this series, are significant features for transparency on data sets used to train generative AI for images, content authenticity tools, “go-along” provenance and credentialing, and integration of workflows. Adobe will continue to upgrade functionality, broaden the scope of use cases, and focus on productivity. Together these will build business cases for wider adoption that Adobe desires.
The desires of a single prominent vendor don’t always drive global buying and adoption. Adobe, and many other software firms, have prospered based on a technical eco-system. The eco-systems are where product development, talent concentration, available services, and compelling benefits interact to enable business cases.
Many software vendors (like Adobe) will see huge costs to restructure/refactor software to integrate newer functionality from AI (and subsystems). Buyers will see software vendors select features for AI-boosted implementation based on ‘benefits for spend’ and ‘what can actually be done’. In customers’ Real World the vendors who produce practical features driving business cases will be sustained. In legacy tech cases where the software is too badly structured or old the products will fade away. In many cases it won’t be a matter of if every competitor ‘gets it to work’ – possibly only one (or none) of a cluster of competitive enterprises will succeed. Customer business cases will drive adoption and long-term success stories.
Software vendors with eco-systems will see growth and learning in their eco-systems even as massive changes roll out from the integration of AI-based tools and techniques. (Microsoft Partners, Apple Developers, IBM Tech, etc.) Upgrades that roil the business economics and models of eco-systems will see failures to rapidly adopt from sheer lack of available services or specific talents. It’s not clear if the productivity impacts from Adobe’s changes will improve business for its tech eco-system or cause much lost brand equity. As an example, if too many users fail to learn how to use new AI-enabled features, or don’t find a compelling economic advantage, then Adobe’s investment in many things AI may not justify its ongoing spend.
Many boutique groups and individuals occupy niches for processes to conceptualize, ideate, produce, and apply commercial art production results. Failures and job losses are likely to result from disrupting these functions in advertising, marketing, consumer experiences, and communications.
If productivity grows by leaps then the talent and services groups will need to become better very quickly to build a new set of niches.
In Part 7 EkaLore will complete our look from a perspective of what Adobe invading their own market will mean across functions and industries.
For more information about Real World Artificial Intelligence and Alien Invaders see http://www.ekalore.com
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