Artificial intelligence (AI) as a service is becoming a reality for more and more consumers, and with the major players launching their 5G services last year, many enterprises across different industries have added AI exploration to their agendas. “The convergence of artificial intelligence with internet-connected machines and superfast 5G wireless networks is opening possibilities across the planet,” according to the Wall Street Journal. This means 2020 could be the year of AI deployment.
By 2030, AI could increase the global GDP by 14%, or $15.7 trillion. Healthcare, automotive, technology and communications, manufacturing, energy and transportation and logistics are the industries with the most potential for impact.
While consumers are benefiting from the implementation of AI across the board, it looks to me like AI presents new challenges for B2B decision makers. According to Salesforce, in 2018, 30% of B2B marketers were using AI “to power the ‘Amazon-like’ personalized customer experiences now expected by business buyers.”
As we continue to shift into the era of deployed AI, I believe B2B players need to have a better understanding of how AI is going to change existing business models and what kind of disruptive scenarios the C-suite will be facing moving forward. PwC predicts that 42% of companies will be investigating AI use this year, while 4% are planning to deploy AI across the enterprise.
Compared to PwC’s predictions for 2019, the intention to explore AI almost doubled this year, while the intention to implement AI across the entire enterprise declined by 80%. This decline could be because companies have already adopted AI, or it could be a result of the challenges that executives have faced in deploying AI.
Enterprises are typically slower to respond to innovation; however, as they are embracing the disruption, the game of being visible for potential customers and finding new partners will likely have to evolve dramatically.
Before the era of AI, decision makers researched the B2B space and prepared the vendors list based on the results, so being visible in search and having a thoughtful content strategy were doing the trick for B2B companies. After widespread AI deployment, a much larger variety of factors will likely have to be taken into consideration. I believe you should be ready to identify the customer segment and the stage of the funnel your customers are in and offer personalized messages in real time.
You also should be continually enhancing your relevance for customers through the lens of AI. Unlocking the journey could be the key to success. Try to find the equilibrium between providing enough content for each stage of the journey and overwhelming customers. The journey should adapt to the simultaneous needs of buying groups (problem identification, solution exploration and requirements building) and ensure fluidity between buying stages. This is where AI can come into play.
According to KPMG, major enterprise organizations have identified “customer and market insights that will refine personalization, driving sales and retention” as one of the high-priority areas for AI initiatives over the next two to three years. With adherence to all the privacy restrictions, it is feasible to expect that AI should be able to better recognize the buying stage where the customer is at a specific moment. Additionally, AI-based content delivery is capable of generating personalized content to create better engagement and addressing decision maker pain points based on all the available data.
B2B marketers are facing the challenge of adopting AI, yet it looks like — with the increasing complexity of the B2B space and customers who expect a personalized experience, content and offers in real time — AI could become a North Star. With the rising volume of metrics that B2B marketers need to decode, they will need a reliable ally, and AI definitely can be on their side.
Accelerating digital ecosystems by redefining the role of each component in response to today’s challenges could be a good place to start with AI adoption. Identifying which parts of the renewed ecosystem keep leveraging the AI and which elements may be low-hanging fruit for AI deployment could be the next step. Creating the road map for AI deployment for the remaining part of the renewed ecosystem can set your company on track for AI deployment.
This article is written by Oksana Matviichuk and originally published here