There’s no doubt that AI systems, platforms, and infrastructure will be all over the business world in the coming years. But what does that actually mean? What does AI business development entail? The challenge is not around implementation but rather how businesses can use AI to create competitive advantage.
Artificial Intelligence (AI) and Machine Learning (ML) have the potential to revolutionize businesses, but it’s more than just cutting-edge technology, it’s about how businesses can utilize it to their advantage and gain the competitive edge that traditional methods of business development can’t provide. That’s where AI business strategy comes in, with companies pushing themselves to find new ways to implement AI and machine learning across all aspects of their business, from marketing and sales all the way to customer service and account management.
Here are eight of the top tips focusing on business development for AI, applicable both whether you’re selling AI systems or working with AI-based platforms.
Catch up on all things AI
Artificial intelligence is not only advancing but also becoming more accessible. Today, a business development executive can easily learn everything there is to know about AI—from how it works to its various applications in different industries. When you understand how technology works, you’ll begin to see new opportunities for your company and be able to recognize patterns where others may not. But there’s no rush—simply understand what’s possible, what’s not, and how AI is impacting other companies.
By learning as much as they can about AI, business development managers will better understand how AI can fit into their sales strategy. The challenge is not exclusively around implementation by data scientists, engineers, cloud architects, etc. but rather how businesses can use AI to create a competitive advantage. For example, businesses are using AI to automate and streamline many of their daily tasks, from recruiting salespeople and account managers to monitor competitors’ activities on social media channels.
So before you decide whether or not an AI-based platform makes sense for your business or that of one of your customers, make sure you’re fully aware of how an artificial intelligence system could work with your overall objectives. For example: Is automation something we should pursue? What type of data do we need? Do we have any restrictions based on our current systems?
Leverage your customer relationships
If you’re selling AI systems, one of the evident ways to monetize them is by cross-selling your existing customer base. That is, integrate with your AI solution and then sell other products or services that are complementary to what they’re using. For example, if you have a solution that helps companies optimize their distribution networks by predicting network latency, think about ways to make it more valuable for your customers by adding weather forecasts or inventory data.
If you work with an AI-based platform (as opposed to offering an end-to-end service), you might be able to get paid if customers use its products successfully to improve their operational and business processes. You could also earn referral fees from helping a company sell AI solutions or find people, via dedicated customer interactions, who can do so. In either case, you’ll need to figure out how AI will fit into your business model in order to create value for yourself and others.
Differentiate on business models
Business models and revenue streams are shifting because of artificial intelligence. As these technologies become more mainstream, companies will increasingly look to services and transactional revenue models to leverage data and advanced algorithms to deliver insights and advice continuously.
This shift to continuous revenue models will happen alongside an overall trend toward more flexible business models that can address high levels of uncertainty in a way that could help companies open up new markets and bring more value to consumers. Ultimately, there is great potential for businesses to develop products and services powered by artificial intelligence, but it’s crucial that they don’t lose sight of what exactly makes their business unique—and how those assets can contribute value at each stage of their model.
The purpose of every business model is to create a sustained source of income while delivering something valuable to customers. If you’re developing products or services with artificial intelligence as part of your business strategy, you need to understand which parts of your business model may be affected by artificial intelligence.
Multiply your communication channels
AI-based products are becoming a part of many industries, and there’s still a lot of room to grow. Whether you’re in sales or business development, it’s important to think about how your product can complement AI and other technology in order to create commercial opportunities.
One way to do that is by scaling communication channels between your customers and advanced customer relationship management approaches. Do they have AI products they need help integrating? Are they looking for platforms with built-in AIs? Thinking like an integrator can help you see new ways to monetize your product, potentially making it more competitive than those who are solely focused on selling their own products.
This could be particularly effective if you have a well-known brand—when customers trust your name, they might be willing to pay extra for support and services. But remember: Always offer added value. It’s easy to get carried away with AI business development ideas and lose sight of what really matters: customer experiences and satisfaction.
When considering artificial intelligence business development strategies, ask yourself: What will my customer gain from using my product alongside AI? If your answer isn’t clear enough that it would convince someone else why using your AI platform makes sense, then you may want to rethink whether pursuing AI integration is worth it.
Adapt and upskill your sales organization
At both B2B and B2C companies, new opportunities in artificial intelligence will demand a shift from products to services and transactional to continuous value delivery model. To adapt your sales organization, and scale sales performance, you’ll need to create incentives that promote these shifts by rewarding sales representatives who take risks on new business models and use AI to improve customer experience.
It means cultivating sales reps who can close big deals but also finding ways to help others succeed in different roles. This is likely to be more of a challenge than adopting new tactics in your marketing and product management organization since sales teams often have strong incentives built into the compensation packages that may make them less flexible when it comes to adapting their role and using different techniques. Also, read here.
Don’t put all your eggs in one basket: Businesses hoping to commercialize AI must find ways to innovate across their organizations, bringing new solutions not just to marketing or product management but also to talent acquisition, human resources, customer service, sales reps, and beyond.
Agile customer services
Agile services don’t wait for a customer to ask; instead, they work proactively to find and solve problems. Customer service agents of tomorrow will be required to possess additional capabilities, such as proactive services, agile knowledge, and capability development of service agents.
Software-as-a-service companies are now able to provide agile and personalized customer services. AI is actually being implemented in order to manage automated interactions with customers. For example, call centers can use machine learning algorithms and natural language processing to learn from their past experiences and suggest a few strategies and give customers suggestions on how to go about getting help with their problems. This allows call center employees more time to devote to other tasks.
Artificial intelligence also helps businesses develop better relationships with their customers by providing them with tailored recommendations. AI also offers businesses a way to monetize AI products by offering them as part of an existing service or as a stand-alone product.
Avoid vendor lock-in, but partner early
The goal of commercializing artificial intelligence in your business is to grow profitably over time. You might partner with a vendor early on, but you need to be ready when things go south—and they will go south at some point. Businesses around what is now known as platforms have had multiple viable competitors in their beginning days, but eventually, one platform wins out and other vendors must adapt to survive.
Consider a scenario where only one company is building and selling self-driving cars—you’d likely end up paying higher prices because there wouldn’t be any competition driving down costs. Allowing multiple players in your space will not only keep you from having to adopt an expensive platform, but it can also bring new innovation into your business.
Not sure how to proceed? Start by looking at what companies are doing today, then look back in history to see how business models evolved. For example, IBM used to sell hardware and software separately until Microsoft came along and started bundling them together. Google did something similar with search engines and advertising.
Then Amazon came along and disrupted both businesses by offering them together again (for a fee). Each evolution was driven by customer demand or technological advancement that made certain business models obsolete or inefficient. While you don’t want to rush into partnerships too quickly, partnering early can help you get ahead of your competition—but make sure those partnerships include contingencies that allow you room to maneuver if things change later on down the road.
Keep up with market changes and evolution
Keep up with AI market changes, shifts in development, and new ideas and concepts. The primary goal is to keep a finger on an AI-specific pulse so you can sell your products or services to businesses that need them, in advance of their needing them.
Pay attention to how people are using artificial intelligence; how they’re measuring ROI; what they’re selling it into, etc. All of these things can inform your strategy moving forward, as well as help you predict needs and opportunities. They also allow you to speak intelligently about AI at sales presentations, future RFPs, and other appropriate times within larger conversations around technology implementations in general.
Key Takeaways
Whether you’re selling AI tools or working with AI-based platforms, here are four tips for AI-driven business success: 1) Understand what artificial intelligence does. 2) Identify potential uses for AI within your industry. 3) Consider implementing an AI platform (but don’t jump into anything too quickly). 4) Determine which services would benefit most from automation (and prioritize accordingly). This last point is particularly important because while almost every company can benefit from some form of automation, not every function needs to be automated at once. Start by determining which services would benefit most from automation and prioritize accordingly; otherwise, you might end up spreading yourself too thin when it comes to resources and budget allocation.
Promote AI as a resource, not a feature. It’s easy to get caught up in using AI as a way to sell your product—but that can backfire. It’s important to not only set expectations about what your technology can do but also how it helps—and then focus on how it improves a customer’s or partner’s existing efforts instead of just replacing their current business process or products.
Use human-in-the-loop AI technologies with enterprise buyers and prospects, partnering with them on problems they want to be solved. AI is great at solving complex problems when you have lots of data, but people are better at making decisions based on incomplete information. Partnering AI with humans can be a powerful combination when you need to solve problems quickly.
Make sure you’re able to explain artificial intelligence concepts simply and clearly. AI has become so much more accessible than it’s almost ubiquitous—but many people still don’t understand exactly what it is or how it works (or even why they should care). If you’re working in an industry where AI is already widely used, try educating yourself on common misconceptions (like AI isn’t real) so you can address them directly when talking with potential customers or partners.
