From Basic Needs to Innovation: Why GenAI Adoption Should Follow Maslow’s Hierarchy of Needs

Over the past year, the emergence of Generative AI (GenAI) has shaken up enterprise IT and become a focal point for innovation. The excitement is understandable – the expected gains in productivity, accelerated innovation, increased competitive edge, and other benefits make GenAI seem like the next big thing. I share the enthusiasm for how it can transform organizations and society. However, as GenAI continues shaping business operations, adopting a structured approach is crucial for success.

Though tempting to dive in headfirst with GenAI everywhere, businesses must address foundational elements similar to Maslow’s hierarchy of needs. Let’s explore the essential steps enterprises should take before scaling GenAI, focusing on holistic technology and people requirements.

Basic IT Foundation

The saying “keeping the lights on” refers to the day-to-day of running a business. Per a Deloitte survey, 57% of IT budgets go towards supporting operations 1. This matters tremendously – CIOs cannot dedicate additional resources and budgets to new activities if they spend the majority of their money on just keeping the lights on

CIOs/CTOs must ensure current IT operations are effective, efficient, and measured by asking:

• Do we have a strategy aligning IT with business objectives?
• Have we set metrics for IT operations and measure investment effectiveness?
• Are we tracking and optimizing enterprise assets like devices, servers, and IoT in virtual, cloud, and physical environments?
• Are we learning from measurements and efficiently adapting to changing technology trends?

Security and Governance

Many companies recognize the need for security but still see it as an IT responsibility. Organizations must bake security and governance into everything, with a framework aligning resources to protect information through policies, centralized accountability, and planning. GenAI relies on provided data, so solid security and governance must come first.

Questions to ask:

• Do we have robust enterprise risk management processes and capabilities?
• Do we systematically evaluate new technologies for risks?
• Do we have the right tools and processes to protect data and IP?
• How do we identify changes needed for GenAI compliance with regulations?

Cloud Operations

Before scaling GenAI, robust and scalable IT operations are critical. A strong cloud strategy supports GenAI by evaluating current infrastructure and identifying improvements to handle advanced GenAI demands.

Basic IT keeps the lights on, but the cloud enables GenAI success. Cloud provides scalability and flexibility for GenAI’s high-performance computing needs without on-premises investments. Further, the cloud manages and processes the large volumes of unstructured data that GenAI requires, increasing performance and reducing data movement/management costs essential for GenAI solutions.

Cloud is not a destination – it’s a way of doing business with agile operations, everything-as-code, shift-left, rapid feedback, and collaboration.

Key cloud questions:

• Do we have an effective cloud strategy that drives business results?
• Have we adopted everything-as-code for development, infrastructure, security, and governance?
• Can we track/allocate IT spend via FinOps?

People

Organizations often say ” People are our important assets “but I am not sure they all fully believe that. Workforce training and upskilling are vital – to boost productivity with or without GenAI, companies need capable employees. This requires cohesive strategy, concerted effort, and solid investment, as the saying goes: “What if we train them and they leave? What if we don’t and they stay?”

Even more importantly, organizations need to ensure people are aligned with the mission and the changes that are coming. I vividly remember the resistance I encountered in the early days of cloud when I helped organizations go through the journey. Here’s an example of a direct question I got from a group of IT folks in charge of provisioning storage: “If developers can just log into the console and create a new storage volume/S3 bucket, what are we going to do in the future?”

Job loss fears are real – IMF estimates 40% of jobs are affected by GenAI, both positively and negatively. 2 You may not lose your job, but it will likely change. Expect resistance but have a plan to guide people through it.

Key questions:

• Do we understand current skills/capabilities organization-wide?
• Have we identified future skills needed for success and gaps?
• Do we have strong Management of Change processes and plans?
• What if some can’t make it?

Data Ops

Data is GenAI’s lifeblood. Think about it. Hundreds of pre-trained models generate correct outputs based on petabytes of training data. Out-of-box models work fine for basic tasks but for organizations to be successful, they need to marry the generic models with their private data. That might be more difficult than it seems. Not because the process is complicated. It’s pretty straightforward to marry LLMs with companies’ data through the retrieval augmented generation (RAG) approach.

We all know the saying “Garbage in, garbage out”. Most companies’ data processes need improvement. Data quality and trust issues, data security and compliance, and data architecture and design areas all need to be addressed before organizations can effectively use private data in their GenAI efforts.

Data questions:

• Do we have data ownership and stewardship processes?
• Are we securing data and complying with regulations?
• Do we have policies protecting corporate/individual privacy?
• Have we addressed ethical, compliant AI use?

GenAI Self-Actualization

Congratulations, you’re ready for GenAI and its immense potential to revolutionize your business! GenAI offers major benefits like rapidly generating content, innovating products, improving decisions, and driving efficiency and cost savings. Research estimates GenAI’s productivity impact at $2.6-4.4 trillion annually – massive gains. 3

Like with everything, enterprises should moderate their expectations based on pragmatic assessment. Organizations must revisit their business and IT strategies to understand how GenAI can drive better value to them and their clients.

Key questions:

• Do we know areas where GenAI improves competitiveness, efficiency, and value?
• Have we built a business case and ROI model for GenAI?
• Is our implementation strategy comprehensive across people, processes, and technology?

Conclusion

We’re still early in GenAI adoption. While 2023 was its coming out party, GenAI is expected to play a major role over the next decade. GenAI can notably decrease expenditures and time in human-centric activities like marketing, data-intensive research, reporting, analysis, and content management. Its robust processing capabilities streamline tasks and enhance overall business efficiency and speed.

But to reap the benefits, thoughtful foundations matter. Like Maslow’s hierarchy, address basic needs first. Lay robust groundwork across technology, people, data, and processes to set up GenAI success.

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1. Deloitte – $1.14 Trillion to Keep the Lights on: Legacy’s Drag on Productivity
2. IMF – AI Will Transform the Global Economy
3. Investopedia – Productivity Gains From AI To Boost Economic Growth in 2024 and Beyond