By Jani Hirvonen, Global Head of Channel Partnerships - Google, San Francisco Bay Area, United States
AI has taken the world by storm since the launch of ChatGPT in November 2022. While machine learning and AI are nothing new and have been around for years, they have become the biggest discussion topic and focus for investments and VC funding in the last two years. While the application of AI is promising and shows great future potential, it is still a bit unclear how different companies and individuals make the best use of AI for diverse use cases.
AI has clear use cases with manual and repetitive tasks with little or no interpersonal elements. This drive towards operational efficiency makes sense in many ways for companies but is also a scary future for a good reason for people working in professions that are potentially under threat. AI does not only touch on the low-value repetitive manual types of tasks but touches also the higher-value interpersonal work where the application of AI can not only increase productivity but also optimize and maximize time allocation for ideal ROI.
One of these areas is sales and account management which relies a lot on interpersonal interactions and relationships but also benefits from data-driven insights to direct the time, focus, and activities optimally for the clients and organization. This “saved” time can then be reinvested in other high-value work. The low-value work can also be automated or deprioritized depending on the goals and needs of the specific organization.
What does this mean in practice then? Think about a world where a salesperson starts work in the morning and looks at the most incredible dashboard which analyzes the sales interactions from a chosen period and provides an analysis of where the salesperson has spent their time partner broken down by types of activities (pitching, troubleshooting), types of interactions (email, Zoom, phone, F2F), types of products pitched and the types of stakeholders that interactions have occurred. The tool then compares all of this to a partner size, growth rate, strategic importance, opportunity size, and product adoption rate and compares this to other partners in the portfolio. Additionally, the tool gives an individual sales executive recommendation per partner on the key areas of focus to maximize the growth, the key interaction types and cadence, and the optimal time allocation per week and day to accomplish this. Finally, the tool does the same for each portfolio, market, and region serving the needs of a higher level of decision-makers.
This is not all though. There are already many third-party software providers that act as virtual sales coaches conducting sales call analysis in customer interactions and providing personalized sales coaching and recommendations for sales executives on how
to pitch more effectively to increase close rates and sales. With personalized coaching plans, AI can empower the sales organization and sales leaders to provide more individualized and personalized guidance for sales executives to improve their game.
The common denominator in both approaches is the need to be able to process large amounts of data and find patterns of excellence in a fast-moving and dynamic environment. As humans, we also do not know what we do not know. Add the key value proposition of AI which is learning into this mix you have unlocked the true power of AI in a way that is hard for humans to replicate.
Another question that arises from this is the role of sales leaders in the future. I do not believe that we will ever be in a world (knock on wood) where people do not need managers or supervisors. However, the role of a manager and supervisor will certainly change as AI adoption and use cases increase resulting in more automation and effective ways of getting the work done no matter what your role is. In short, the value proposition needs to change and evolve, and for sales leaders, this means in the first place being able to leverage AI solutions to drive growth and revenue and leverage the data and insights that these solutions provide to change the behavior of their salespeople. This is also a mindset shift as completely new things need to be learned and, in many ways, sales leaders are forced to get out of their comfort zones like everyone. In the second phase, sales leaders need to learn to design AI-driven solutions and strategies and be able to implement them effectively in their organization.
While doing all this we constantly have to keep ourselves checked against the goals or our organization and be especially conscious of the cost and feasibility of implementing and or building an AI solution. AI is not an answer to everything and a cost-and-benefit analysis needs to be done regularly. Sometimes this can be an exercise or trial and error and proving the use case first before scaling further and investing more resources if the benefit and ROI of AI are still unclear.
In many ways AI resembles globalization, the adoption of mobile phones, and the adoption of the internet in their times in history. However, this time the growth is even faster and more exponential and in many ways the train has left the station and you can choose whether you are on it or not (but it is not coming back). We are still in the early stages with AI but beyond the usual use cases of automation and increasing operational efficiencies, AI can be a powerful tool for creating the next-generation sales force by helping to optimize sales executives’ time allocation more effectively, customizing their pitches to maximize revenue and developing better sales skills while making the partners happier than ever.
However, this all requires sales executives and sales leaders to evolve and learn new skills to evolve and create next-level sales excellence in their organizations and beyond.
