How Should Enterprises Allocate Their GenAI Budget?
Before an enterprise makes any kind of investment, a degree of strategic planning is always inevitable – from knowing how much to spend, to allocating resources for successful implementation. When the investment in question relates to a Generative AI tool or software, this planning is detrimental for success – it can be the difference between merely experimenting with GenAI, and achieving tangible, long-term business growth from these cutting-edge systems.
We’re about to delve into the details that any enterprise ought to be aware of when setting aside a GenAI budget, explaining why it’s not just about having the funds; it’s about allocating them effectively to drive meaningful outcomes.
Key allocation areas for a GenAI budget
We’ve rounded up 4 high-priority considerations for any enterprise investing in GenAI, summarizing the factors that your GenAI budget should account for within each aspect.
AI model testing
Ensuring the reliability, accuracy, and fairness of systems during the GenAI development is an unavoidable step in the pre-implementation stage, and your GenAI budget should be used to lay the foundation for this.
The scope needed to ensure these values are upheld during the entire GenAI output production line involves developing comprehensive testing frameworks, including simulated environments and real-world scenario testing. The results of these tested outputs is invaluable, as they’ll highlight risks such as data inaccuracies and bias. At this point, feedback loops can also be devised to incorporate insights from real-world usage into model refinement.
The resources allocated for testing should also cover investment in tools and technologies for continuous monitoring and validation of AI models, as these processes will require periodic iterations. Our GenAI development platform has been designed to support testing processes, with dynamic governance capabilities which allow for GenAI visibility over compliance and data validity; complemented perfectly by the built-in data training functionality to give teams more control over output creation from start to finish.
Data privacy measures
Every enterprise has a responsibility to ensure data privacy and compliance with territorial regulations (i.e, GDPR and CCPA), and ensuring your GenAI usage doesn’t infringe upon these standards is crucial. Budget allocation for robust data anonymization techniques, encryption methods, and access controls is necessary to adhere to these types of policies, and not making this consideration would be a costly mistake for any enterprise.
Your GenAI budget also needs to be used to develop data governance frameworks, and to account for regular GenAI system audits to ensure data integrity and security throughout the output lifecycle. This includes implementing encryption algorithms to secure data both at rest and in transit, anonymizing sensitive information to prevent unauthorized access, and establishing access controls to restrict data access based on user roles and permissions.
Our GenAI data security platform offers advanced encryption techniques, anonymization tools, and access control mechanisms to safeguard sensitive data and ensure compliance with privacy regulations.
Governing GenAI applications
Setting some of your GenAI budget aside for governing applications is an essential consideration for enterprises. The consequences of not making this provision vary from proliferation of inaccurate, false information, to irreparable reputational damage, and exposure to cybersecurity attacks. According to our State Of GenAI Survey, these risks are currently the most frequent culprits holding enterprises back from fully investing in GenAI, but their occurrences can certainly be kerbed when transparency and oversight is maintained over all applications.
The ideal environment for GenAI usage is one in which enterprises know exactly when and where GenAI is being used internally, and they also need to understand who is responsible for deployment. By governing GenAI usage to this extent, risks can be mitigated, allowing GenAI tools to deliver optimal results. Effective GenAI governance strategies ensure that the entire process follows protocol – for example, the individual deploying GenAI has received sufficient training, they’ve acknowledged any unintentional biases at play, and the GenAI model they’re using has been refined to produce high-quality, trustworthy outputs. In this way, governance has been followed by the individual, but it’s also embodied in the systems; this is a core element of the capabilities offered by our own platform.
Monitoring usage
GenAI usage creates its own internal trail, and insights from actual deployment can serve as opportunities to both manage risk and optimize operations. One of the biggest red flags that we associate with unmonitored GenAI usage is shadow AI; where systems are used in an ad-hoc or unsanctioned manner. Any unwarranted usage of GenAI can create new instances of bias, and when they haven’t been acknowledged, they can skew the quality of outputs. Unmonitored GenAI can also pose regulatory and compliance risks, as it doesn’t demonstrate any adherence to best practices. On the whole, it’s also a simply inefficient way for enterprises to use GenAI, as overall reliability becomes compromised when GenAI tools are used for ad-hoc tasks, whether they serve a valid business purpose or not.
When enterprises set budget aside for GenAI visibility and monitoring applications, it enables them to identify any anomalies in usage patterns, such as shadow AI, giving them a proactive approach in challenging and resolving these incidents. These insights can also reveal opportunities to optimize deployment, by giving enterprises a clear overview of where GenAI is generating the most impactful results; and vice versa, where it isn’t necessarily being utilized to its fullest potential.
GenAI employee training
At the core of any GenAI implementation effort, you’ll find an empowered, skilled workforce that can lead deployment with total confidence. As such, it’s also the responsibility of the enterprise to promote and encourage a culture of learning around GenAI technologies. Your GenAI budget should support employee access to comprehensive training programs to upskill employees in GenAI best practices, giving your workforce the knowledge they need to produce accurate outputs.
When this learning is nurtured, it can open up opportunities for specialized training for data scientists, engineers, and business stakeholders, fostering a culture of GenAI literacy and proficiency that isn’t excluded to a certain minority.
Your enterprise GenAI education curriculum could include providing training sessions, workshops, and certifications covering various aspects of AI, such as machine learning algorithms, data preprocessing techniques, model deployment, and ethical considerations. It’d be advantageous to include hands-on experience with the GenAI tools and platforms that your team will be working with, as this is a prime opportunity for questions off the back of real-time experiences with your systems.
We’re helping organizations to cultivate a workforce that is well-equipped to drive GenAI initiatives forward with our GenAI education software. Within our platform, we’ve created training modules and educational resources that empower employees with the knowledge and skills needed to leverage GenAI effectively.
Incident response planning
GenAI-related incidents are inevitable, so proactive planning is a must. Allocate some of your GenAI budget into creating protocols for these incidents, and provide training provisions for incident response within teams and on an individual basis. By doing so, you’ll give your workforce the upper hand in the face of any unavoidable outcomes that warrant a swift response to manage any associated risks.
Alongside practical incident response skills, enterprises also need to invest in the right visibility solutions to oversee and preempt these scenarios where possible. Investing in a tool that allows for real-time monitoring, detection, and mitigation of GenAI-related risks is a great step, and our own platform offers all of these incident-related features. Anomaly detection, threat management and escalation are all provided within our platform, making it an indispensable tool for any business that is aware of the risks that come hand in hand with GenAI.
How to prioritize your GenAI spending
A smart GenAI budget accounts for a breadth of timelines – from pre-implementation, to long term sustained GenAI usage. We’d recommend prioritizing your budget to focus on each ‘stage’ of the GenAI lifecycle – from initial model development and testing, through to long-term, bigger picture considerations such as employee training.
Given the nature of the technology and its susceptibility to external factors, your budget allocation will need to adapt to different requirements. GenAI presents an equal measure of opportunities and challenges, but using your GenAI budget to learn from these scenarios will differentiate your enterprise from those that are stuck in the ‘experimentation’ rut.
Set the right kind of precedent for your GenAI investment by investing in the right areas from the outset, this way you’ll be able to maximize returns and minimize risks
Choose the Portal26 GenAI TRiSM platform for your enterprise
We’ve created a platform that gives enterprises access to all of the insights, escalation capabilities, and performance metrics that they need in one, simple view. Our GenAI platform is the ideal choice for enterprises that want to embrace the technology with total assurance in its usage. To arrange a demo, simply contact us today.