The real challenge to meet the expectations of artificial intelligence (AI) has little to do with technology.
It’s all in the approach…the mindset.
The environment you create has a significant influence on just how much you can capture of AI’s vast and growing potential.
That’s why this checklist is not about whiz-bang features and wicked-cool capabilities. Those exist—for sure—and they’ll continue to expand as innovation does in the months and years ahead.
No, this checklist is concurrently more and less than that…
The AI Foundation and Prerequisites
It’s about high-level foundation. And, while yes…it seems simple, don’t just toss this list aside.
Really consider what you have in place already and the holes that may exist.
Now, be honest. This isn’t an exercise you share with us…or any vendor for that matter.
What we’ve learned is that the companies that take this step—the ones that address these foundational milestones—end up being our clients that get the most out of their technology investments.
And when it comes down to it…artificial intelligence is really just another piece of enterprise tech, eh?
The Three AI Prerequisites
In our last post, we identified the cultural and philosophical preparations a company should have in place to get the most out of enterprise-grade AI technologies:
- A long-term business and IT vision
- Clearly-defined business and IT goals
- A collaborative culture
Since they are as important as they are related, let’s dive in a bit on the first two areas together: Vision and Goals.
Then, in the next post in this series, we’ll detail building out that collaborative culture and why it’s a common component of organizations that successfully implement artificial intelligence technology.
Long-term Business and IT Vision (Prerequisite #1)
The foundation of a successful AI implementation is a clear, long-term vision that addresses both business and IT needs.
That means creating the roadmap that details exactly how AI fits with your current and future business processes, as well as IT environment over the next three to five years.
This takes a good amount of thought and perhaps even more detail.
For example, if you generally have discreet, isolated problems to address, traditional software applications likely fit the bill. Conversely, if your business needs require multiple systems, functions, and/or departments, then you likely have (or should consider) technology that can integrate systems of record and coordinate actions across the entire organization. While this is NOT what AI does per se, it is critical to understand the current and potential future ecosystem. Envisioning—in great detail—how your business will operate in the post-solution state is key.
Why? Vision—and especially a complete vision—is important to meet the potential of AI. Largely, this is about uncovering all the opportunities for generating machine-based efficiencies.
This is where becoming a leader begins. Think about it…the world’s top-performing companies are largely recognized for having a complete vision. Fortunately for the rest, there’s Gartner’s Completeness of Vision rating. This criteria for their various Magic Quadrant analyses provides a standard…a basis for what vision entails for a large enterprise. And so…
Seven Components of a Vision
To create a well-developed vision, make sure you consider these components:
- Business challenges and potential challenges
- Solutions to address these challenges—both in place and future
- Resources and potential resources needed
- Current methods and ease of changing them, if necessary
- Processes and practices in place
Clearly-Defined Business and IT Goals (Prerequisite #2)
If vision is about the destination, goals are the building blocks for actual success…the milestones that—if reached—can transform your vision into reality.
No matter the framework you choose to create your goals, it’s not enough to hold only yourself, your teams, and your business accountable:
- Share your goals
- Make sure both you and your vendors are continually working toward them
- And, keep everyone involved accountable for their achievement
While AI can continuously adapt to evolving business goals and progress, it cannot define them for you.
Before starting down the AI path, define the right outcomes based on that vision you laid out.
And by all means…hold your vendors to the same standard.
For example, consider Amtrak.
Amtrack and AI
Amtrak’s high-level vision was delivering an exceptional customer service experience…one that empowers their customers to self-serve without compromising a truly personalized experience.
With primary goals of eliminating a customer’s need to call or email a representative, as well as improving the customer experience during booking and reservation changes, Amtrak also needed a scalable solution that could handle the high transaction volumes of peak traffic periods.
With a clearly defined vision and measurable goals set, Amtrak worked closely with their chosen vendor to deploy an Intelligent Virtual Assistant with the capabilities to meet their specific goals.
The end result? Delivery of the personalized experience Amtrak customers now expect…with an efficiency far greater than traditional customer service channels.
Successful deployment of AI…or any long-term technology…requires company leaders to know the destination and what they want to gain from the journey.
But, there’s one more thing needed to make your AI movie come together.
Stay tuned for the final post in this AI series: Building the Team. Until then…