Understanding the Impact of GenAI on the Future Workplace’s Licensing Needs
Do you need to optimize GenAI expenses? Find out how to monitor usage, stay updated on pricing, and prevent shadow AI.
Brian Adler, senior director of cloud market strategy at Flexera, discusses the importance of GenAI in the future workplace. He advises assessing use cases, licensing implications, business needs, and IT infrastructure management.
Across industry verticals—in financial services, healthcare, and well beyond—organizations are rapidly embracing large language models (LLMs) and generative AI (GenAI) for the use cases that help drive workplace transformation. McKinsey & Company has written that the “future of work” is “an informed perspective on what businesses and other organizations need to know about how work could shift (given digitization and other trends), plus how workforces and workplaces can prepare for those changes, big and small.” That informed perspective requires businesses of any size to establish guardrails for managing GenAI and the associated software licenses as part of the overall IT estate.
Preparing for GenAI Licensing Impact
Technologies need to be incorporated in a way that supports the transformative power of AI-driven initiatives that your staff requires while also supporting effective IT asset management (ITAM). This approach keeps an eye on the true expenses associated with the initiatives while also meeting the specific needs of the workforce. Consider three important steps for preparing for the licensing-related impact of GenAI functionality.
1. GenAI integration: evaluating your team’s license needs
Understanding how GenAI and its use cases may impact the licenses your team needs is crucial.
Consider this scenario: your staff is looking to shift some responsibilities and initiatives to the GenAI functionality now available through the newest versions of a vendor’s software. Your current software licenses, though, may not include the GenAI capabilities. Your perpetual licenses never will; you paid once for unlimited use of the existing software.
If you want all the fancy, attention-grabbing GenAI features that promise the innovation your organization wants, you may need to switch licensing models. This may mean moving to a subscription, for which you pay monthly or annually and may receive access to upgraded features. That perpetual licenses may not be viable long-term if they don’t include GenAI functionality is one of the “perpetual licensing risks of generative AI,” as identified by Gartner Research in November 2023.
Because multiple deployment and monetization models remain viable, software buyers must be proactive: pay close attention to what you’re purchasing and what GenAI functionality those licenses include. This is particularly important as software vendors and buyers alike embrace software-as-a-service (SaaS) deployments and subscription monetization models.
Be aware of the expenses related to switching to licensing models that deliver GenAI, as well as the implications of using more restrictive licenses that may not deliver the functionality you need or likely will need. Clarity in expenses and terms will help you optimize the associated licensing costs.
See More: Getting Real About Gen AI: What You Need to Know
2. Optimizing GenAI adoption: strategic considerations for license investment
As workplace needs shift, consider which specific users in your organization might need the generative AI services available from your software vendors. This is a good example of how to evaluate the potential impact of GenAI on the future of work—along with the potential ramifications for your IT estate.
Pricing may be fixed, per user per month, with required annual subscriptions, potentially driving huge costs for your infrastructure. This expense may not be necessary to achieve your workplace goals. Before purchasing additional licenses, consider the following:
- Who in your organization needs an AI tool? Invest only in what your staff truly needs to avoid wasted spend.
- Is the tool you’re considering the best one for your workforce? Evaluate your alternatives. Whether or not a particular LLM or generative AI tool is best suited to what your staff needs will be based on factors such as your level of adoption of a particular vendor’s solutions across your organization; the ease of integration and reporting may be worth the expense. Options are available from multiple vendors, including a host of startups with competitive options, often with free trials. Decide which fits best into your IT portfolio and which best meets internal requirements.
- Who on your team can derive the greatest benefit from the tool? Beware of automatically adding this functionality to all of your existing subscriptions. Even if you believe that the ROI on a particular tool is worth it, begin by implementing it just for the core group that truly needs it. This might be your top execs, your best data scientists, or your top-performing sales team members. Begin by purchasing the licenses for this core group, then base your broader adoption strategy on the experiences of these early adopters and the anticipated needs of your organization.
See More: Why GenAI Implementation Requires Collaboration
3. Managing AI sprawl: asset strategies for future workplaces
Inventory your assets to prevent sprawl—including AI sprawl—in your evolving workplace. When your workplace is on the cusp of a major shift toward AI, it’s a particularly important time to have a clear view of your entire IT estate:
- Rely on ITAM best practices to maximize the value of your technology investments. An enterprise technology blueprint offers a data foundation that can help you clearly evaluate your organization’s technology environment.
- Know if GenAI is part of what you’ve already licensed. Be aware of the associated end-user license agreements (EULAs). Whether GenAI is included or is an add-on feature and expense, make an informed decision about needs, costs, and cost optimization.
- Know what your entire staff is consuming, which will inform decisions about whether or not to transition to subscription and/or SaaS. Perpetual licenses may be more restrictive, in the case that you may not get all the GenAI capabilities that would be rolled out with a subscription model. Also, evaluate what is approaching end-of-life/end-of-support (EOL/EOS) status and the potential implications for the protection of data tied to your perpetual licenses.
- Optimize AI expenses and value over time. Visibility into usage data and monitoring internal adoption is key, particularly as staffing needs and responsibilities may be shifting. Pay close attention to vendors’ contracts, the licensing models, and each vendor’s market strategy. Since these are early days for most vendors, the licensing and pricing models for their GenAI catalogs may change rapidly.
- Guard against AI sprawl and/or shadow AI, in which employees use and install chatbots and popular AI tools on their own, bypassing IT and potentially undermining organizational security initiatives.
Generative AI offers opportunities for innovation. Your workplace needs a viable approach for managing GenAI, as well, to effectively drive the future of work.
How can GenAI implementation affect IT infrastructure, and what steps organizations should follow to ensure a smooth transition? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
Image Source: Shutterstock
MORE ON ASSET MANAGEMENT
