From ideas to impact: 3 steps to scale AI opportunities in digital sales

Let’s get the obvious out of the way first: scaling AI in digital sales is not as simple as ticking off three boxes. But when it comes to moving from experimentation to real business value, certain principles can make all the difference. In this blog, we’ve gathered three essential steps to help you get started with scaling AI in a way that delivers real business impact.

The promise of AI, especially generative AI, is hard to ignore. The sheer number of use cases, success stories and new tools being launched daily is both exciting and overwhelming. Most leaders see the potential of smart AI agents and automation. But according to Harvard Business Review, 80% of AI experiments never make it to production. 

So, how can your organisation be among the successful few who genuinely innovate, implement and create a competitive edge in digital sales? We’ve broken it down into three clear, practical steps that will help you scale AI in digital sales

Step 0: Understand the art of the possible

This is a hygiene level for any change, and there is a good chance you have already taken this step: to envision a change, you need a solid grasp of what the technology can actually do and its limitations. Understanding what new tech enables and where it is feasible makes it possible to apply it to unique business problems and opportunities.

Most business leaders and digital sales experts are quite well-versed in the possibilities of AI in commercial customer journeys, especially after the rise of generative AI tools like ChatGPT. Many have dabbled with use cases or run proof of concepts (PoCs) to familiarise themselves with the tech. 

Tech vendors, consultants, and advisors have also contributed to driving awareness, making this "hygiene step" fairly widespread. But understanding must go beyond surface-level use. You need to connect the dots between AI's potential and your specific business challenges and opportunities.

Step 1: Shift from tech experimentation to changes grounded in strategic objectives

Enough with the AI PoC exercises and experiments! The technology is mature enough, what matters now is using it with purpose.

Most PoCs were designed to educate, raise awareness, or test feasibility. They've served their purpose. But if your AI initiatives aren't tied to strategic goals, they'll stay stuck at the pilot stage.

So, how do we capitalise now on this powerful and proven new technology? Like with any other investment, assess its impact on your strategic goals and build a business case. Start by asking the questions:

• Why are we doing this?
• What strategic goal does this support?
• What metric will it move?

Let’s say your top priority is increasing customer loyalty. Focus your AI investments on improving user experience, enhancing service quality, or creating more engaging interactions. On the other hand, if customer acquisition is the bottleneck, look into how AI can automate lead qualification or personalise marketing journeys to boost conversion.

Anchor every AI initiative in the business outcome it’s meant to drive.

Step 2: Ground innovation in real-world processes 

To make AI stick, embed it into the core of your customer and business processes. Don’t treat it as a separate innovation stream. Look at the full customer journey and identify where change can have the biggest impact.

This is also the perfect step to build organisational buy-in that helps adopt new ways of working. Bring together cross-functional teams that work across the customer journey. Build a joint understanding of current issues, opportunities, and bottlenecks and ideate for change or even transformation. 

We often see that AI initiatives are easily focused on incremental change, enhancing current processes or making them more efficient. But don’t stop there. Step back and ask: what would this look like if we redesigned it from scratch? By looking at the end-to-end process over the organisational silos, it is easier to ask bolder questions. Challenge your teams to consider what your service would look like if Google made it. 

Step 3: Create a roadmap for scaling digital sales with AI

Okay, so now you have your key strategic objectives clear and issues and opportunities in end-to-end processes mapped. What next? Now, the fun part starts! 

This is where all the early PoC experience and tech awareness pays off. Match identified opportunities with real tech capabilities, whether in-house or available through vendors. Use these capabilities as a toolkit for your teams to explore what's possible.

Based on those templated AI tools, ideate and describe innovations that will solve the customer journey or process bottlenecks or enable opportunities to improve. The list of innovation ideas is now your backlog. As it is based on strategic goals and real processes, it should be a business-driven backlog, not a list of cool tech experimentations. 
There are multiple ways to turn that backlog into a roadmap. Typically, it's beneficial to start by evaluating the impact, effort, and probability of that impact. Below are useful rules of thumb for developing the roadmap:

• Evaluate each idea by impact (customer value + internal efficiency), effort, and confidence level.
• Start with quick wins and urgent fixes.
• Plan for longer-term initiatives that may need more time or resources.
• Work in short iterations, think weeks, not months or years.

Turn strategy into action

Sounds like a plan? Sure, but how do you do it in practice?

Based on our work with leading Nordic companies, we have created the AI opportunities in digital sales canvas to help you take concrete steps towards scaling AI in digital sales. 

Read more here and download the AI opportunities in digital sales canvas here.