The hype surrounding AI is real, but so is the complexity. So if you’re feeling unsure of how to get started with generative AI for your business, you’re not alone.
The key to effective implementation lies in asking the right questions at the start, so you set your organization up for long-term success.
Getting Started With Generative AI: The Current Landscape
There’s undeniable excitement around generative AI and all its possibilities right now, but with that excitement comes an expectation of quick results. Leaders may have leeway to experiment in this area, but they’re under a lot of pressure to find immediate cost savings.
Of course, short-term wins aren’t a bad thing; we all want to see a fast ROI when we can. But getting started with generative AI requires a measured approach.
AI isn’t a quick fix for most business challenges. The real benefits often appear over time as teams accumulate incremental knowledge with specific tools and applications. In other words, implementing generative AI is more of a marathon than a sprint.
Obstacles to Getting Started
Adding to the complexity of getting started with generative AI, sifting through the sheer number of tools and options available can be overwhelming. Plus, once you express an interest, you’ll be inundated with waves of varied advice, opinions, methodologies, and articles on what and how you should implement.
Further, you’ll likely encounter a discouraging claim that getting started with generative AI will take a year or more to allow time to get your data where it needs to be. Meanwhile, your legal department may be hesitant to greenlight generative AI initiatives, preferring to wait on what they perceive as a potential risk.
The truth, however, is that all these obstacles have possible solutions, especially when you take a long-term approach.
Look Beyond Short-Term Gains
When getting started with generative AI, you’ll certainly notice some short-term efficiency gains in areas like software development, customer experience, or knowledge management. But short-term gains accompany almost any new technology.
With generative AI, however, long-term success doesn’t go to those who simply implement it first. It goes to teams who analyze and experiment over time until they deeply understand the cycle of learning, training, and optimizing their AI tools with the best possible data.
Taking the time to thoroughly train internal teams and develop AI competency within your organization sets you up for long-term efficacy and agility with one of the most powerful tools to enter the market in recent memory. Partnering with external experts can also provide practical, experience-based insights both in training and implementation, helping you avoid blind spots and plot a course for the highest benefit.
While there’s nothing wrong with enjoying quick wins, getting started with generative AI is more akin to building a muscle — which takes time. The risk of focusing solely on short-term thinking, especially at the executive level, is finding yourself playing catch-up later when competitors have been experimenting, learning, and training their people on these technologies.
Rethink Value Creation With Generative AI
To truly set yourself up for success with generative AI, step back and consider how your company creates value and how people work. Instead of just trying to shoehorn AI into existing processes, think about how it might fundamentally change your company operations, or even your industry.
This shift in perspective applies across all industries. For example, in marketing, generative AI could transform everything from content creation and personalization to predictive analytics and campaign optimization. The key is to look beyond obvious applications and consider how AI might reshape your entire value chain.
While some use cases, like personalized marketing or software development, apply across industries, others offer unique, niche capabilities. Below are just a few to get your brain storming:
Financial Services
- Fraud prevention with synthetic data
- Risk management
- Advisor assistance
Insurance
- Underwriting assistance and recommendations
- Claim processing and settlement
Healthcare
- Clinical documentation automation and summarization
- Workflow automation for patient messaging[A1]
Retail
- Personalized shopping assistance
- Image generation and augmented reality
Industrial
- Technician training and knowledge retention
- Warranty claims automation
Media and Entertainment
- Democratization of content creation
More accurate personalized advertising for target audiences
3 Questions for the Long-Term Approach
Who Are You, Really?
To get started with generative AI, take a long, hard look at your company and think about how you make money and create value. How big of an opportunity — or threat — does AI represent?
If your business creates value primarily through unstructured data (like content creation or on-demand design), you may face more disruption. An on-demand graphic design firm, for example, faces a significant competitive threat from AI image generators.
Seek to understand how AI impacts you, how it disrupts you, and start looking for advantages.
Where Can You Expand Your View of Data?
Preparing for success with generative AI often requires adjusting your processes and expanding your view of data. Look at your end-to-end value creation and consider:
- Where does data currently play a role?
- Where could data potentially add value?
- What data aren’t you capturing that could be valuable?
In investment management or private equity, for instance, generative AI may help you capture and analyze the rationale behind investment decisions — not just which investments were made, but also why others weren’t. This wealth of previously untapped data could lead to more informed strategies and better outcomes.
How Will Getting Started With Generative AI Affect Your People?
Getting started with generative AI isn’t just about the technology — it’s also about people. Many organizations are buying AI tool licenses without seeing the expected adoption or uplift, highlighting the critical importance of change management.
Not everyone is comfortable thinking in terms of vast amounts of data or considering all the data points needed to make a decision. These are new ways of working that require investment in training and process adjustments. Don’t underestimate the effort required to drive adoption and integrate generative AI into your workflows effectively.
Generative AI: Your New Digital Intern
Some of what will determine the ultimate success of generative AI adoption for your company involves how you treat the technology.
Generative AI is not an executive, a team lead, or even a technical expert. No, generative AI is your new digital intern.
It may be analytically strong and a quick learner, but generative AI has low emotional maturity and limited knowledge of your specific business. Like a human intern, it requires management, training, and patience. You wouldn’t expect an intern to deliver perfect results immediately, and the same applies to generative AI tools.
If you approach getting started with generative AI with expectations of immediate, flawless results without investing time and effort, you’re setting yourself up for disappointment. More importantly, you risk falling behind competitors who take a more measured, long-term approach to building AI capabilities.
Final Thoughts on Getting Started With Generative AI
While the hype around generative AI is intense and the pressure for quick results is real, true success lies in playing the long game.
Getting started with generative AI isn’t about rushing to adopt the latest tools. It’s about making informed decisions that align with your company’s value creation, data ecosystem, and long-term goals. This isn’t a sprint — it’s a marathon that requires patience, strategic thinking, and a willingness to learn and adapt.
Remember, the real winners won’t just be those who implement generative AI first, but those who learn to harness its power most effectively over time. Start building your AI muscle now, and you’ll be well-positioned for whatever the future holds as this technology evolves throughout industries.
Interested in mapping what AI could do for your organization? Contact us for an AI readiness assessment!