How to Sell AI to Your Enterprise
Selling AI as a powerful solution for your enterprise is not always effective. Here’s how to focus your pitch to improve the chances your AI project will be funded.
- By Troy Hiltbrand
- January 3, 2019
Are you continually frustrated trying to unsuccessfully convince executive leadership that your enterprise needs AI? Do you feel defeated because you hear everywhere in the news that AI is one of the most impactful technological breakthroughs of the modern era but can’t get anyone else to pay attention?
The answer to this is to not give up on AI. Revise your approach to be more effective at connecting the dots for your business stakeholders. To optimize your AI pitch, focus on two specific areas -- business value and scalability -- and use the right terminology.
Business Value
Don’t try to sell AI as a solution to your enterprise. Instead, demonstrate the value implementing AI can achieve. AI is a field of study that encompasses many subfields, each of which can deploy different technologies and concepts to make a business more effective and efficient. Just as you would never try to sell mathematics to a business as a way to make it successful, go beyond selling AI and explain what implementing AI will mean in a tangible, impactful, bottom-line way.
Identify where the business could be enhanced with AI and present these use cases to executives. Three main areas where businesses can effectively employ AI include enhanced insights, improved user experience, and optimized process improvement.
Enhanced insights. Business users already regularly gain insights from reports, metrics, and analytics. By applying such techniques as optimization, forecasting, prediction, and fraud detection, you can further enhance the value of these insights. Mass personalization mechanisms, enabled by AI, allow you to optimize how these insights are delivered. AI has the potential to dramatically increase your BI’s impact by delivering the right information to the right people at the right time to make the best decisions.
Improved user experience. The next place to look for use cases is with the user experience. Natural language processing and natural language generation can completely transform how your end users engage with your environment. Chatbots can make the interface intuitive and conversational. If you work in an international environment, machines translation can provide users familiar content at a speed not previously achievable with human translation.
Optimized process improvement. Your business is made up of multiple processes. Another treasure trove of use cases is within the flows of these processes. As you model your processes and identify areas where the flow gets stuck or slowed down, you’ll identify opportunities to apply AI. Some of these steps can be completely automated by applying machine learning to evaluate incoming data and allow the system to make the decisions without human intervention.
If those steps cannot be automated and require human-to-human interaction, conversational chatbot technology can expedite that transaction by being a broker between the parties ensuring that the process moves along as quickly as feasible. If those steps require human-to-machine interaction, opportunities to connect those machines into the ecosystem (aka the Internet of things) can greatly optimize the process.
Scalability
Once you have identified the business value of using AI in your organization, determine the scale of your initiatives. Frequently, applying advanced analytics to small components of systems can have big benefits. Instead of trying to take on a massive AI program, start small, monitor the contribution to your organization’s goals, and grow from there. Take on pilot projects to assess your organization’s readiness and maturity and your staff’s skills and aptitudes. This iterative and agile approach will help you to establish a stronger business case for future larger and more widespread AI projects.
Using the Right Terminology
Although the term AI is in vogue in the media, users and executives alike may be concerned about AI’s potential negative effects on society as a whole. If you sense hesitation, look for other ways to describe the technology. Terms such as assistive intelligence, augmented intelligence, or intelligent automation can be used in its place and avoid the preconceived biases associated with AI. The goal of altering your terminology is to better describe how the implementation of AI technology will assist your business and without using terminology that invokes fear arising from predictions that AI will rob jobs and enslave society.
A Final Word
As you look at enterprises large and small that are effectively applying AI in their business models, you may become excited to imagine what it could mean for you and your business. If you continue to run into a brick wall each time you present AI to executives when seeking AI project funding, revise your approach to focus your pitch on value and scale and use terminology that improves your chances at success.
About the Author
Troy Hiltbrand is the senior vice president of digital product management and analytics at Partner.co where he is responsible for its enterprise analytics and digital product strategy. You can reach the author via email.