5 Questions to Kickstart AI Implementation

In our last Strategy Collaborative Ask Us Anything session, we covered common questions related to AI implementation in your organization.

This is certainly not a comprehensive guide for AI implementation in your organization! A comprehensive AI implementation is influenced directly by your organization’s strategic approach to AI, how it will impact creating value for your customers, improve the productivity for your team, and transform how to assemble your organization.

But the time to implement AI in your organization is NOW! So, we’ve pulled together these common questions to answer as a first step to get your organization thinking about using AI to accelerate your current outcomes and business objectives.

Question 1: What Impact Will AI Have on Your Organization? Will It Be Disruptive?

This question has probably been top of mind for many leaders since the rapid emergence of AI in the market over the last year.

Unfortunately, it is a challenging question to answer, as the potential disruption AI will have on industries can vary between not disruptive and extremely disruptive. It’s up to each organization to figure out where they will fall on the continuum.

Consider the impact e-commerce had on businesses in the early 2010’s. Online commerce started small and only impacted specific businesses. Over time, the technology transformed more industries and sectors until it became a default way for many businesses to…well…do business. Now almost every company, whether they are B2B or B2C, utilizes e-commerce as a viable business option.

The unique feature that sets AI technology apart from other disruptive technologies is that it’s disrupting society not just at an industry level, but at a sociological level. AI is quickly becoming more widely accessible to the average person in a way that other technologies haven’t been in the past.

For example, generative AI, such as ChatGPT, became an overnight sensation (and disruption) that impacted not only corporate industries but also academic industries. Schools and universities suddenly found themselves grappling with this new tech. They had to quickly find ways to address the potential issues that this technology posed, while also learning how to leverage the opportunities and encourage exploration within their classrooms.

The big takeaway? AI isn’t going ANYWHERE.

Question 2: How Can We Mitigate the Disruption AI Implementation May Cause?

Think of adopting AI more as an investment opportunity rather than a disruption – even though, yes, it will be disruptive on some level. However, when we shift our mindset to think of AI as a tool to invest in, we begin looking at it through a lens of opportunity and advantage.

To get started, use the power of AI in your existing processes

As we said earlier, this is not a comprehensive guide for AI implementation. But, to get started, we recommend identifying 3 or 4 small-scale ways to incorporate AI as a test or prototype in your organization.

For example, using AI to help automate your administrative tasks is a good place to start! As you get your results back for each initiative, you’ll know where the value of your investment is best applied for the biggest impact.

As you start implementing it into your team’s current processes and tasks, a best-practice is always having a framework for measuring its impact. This might include:

  • Tracking data on efficiencies gained.
  • Keeping tabs on what tools your teams are using and the pros and cons of each.
  • What use cases you’re applying AI for.

As you test and prototype, it might also be helpful to assemble an AI team, committee, or champion in your organization to lightly manage the process.

Question 3: How Do You Move Leadership to Accept Implementing AI in Your Organization?

Building a personal relationship between leadership and technology is crucial. Leadership needs to understand what AI is and how it can benefit the company. Starting with accessible tools, like chatbots, can help leadership grasp the potential of AI.

When we see the data and its effectiveness, and we gain an understanding of how it impacts our organization, then we are more likely to support AI initiatives.

The focus should be on the business aspect rather than just AI. It is imperative to align your AI solution with the broader business strategy.

Frame your AI implementation strategy as a means to achieve business goals, such as improving the buyer proposition, expanding into new territories, transforming the business, or even just improving efficiency.

Run your entire team through an exercise where you consider which AI tools can help you save 5 hours a week and how you can pilot them this week. Take a few days to test them out and see what your team thinks!

What are some of the top fears perceived by leadership as it relates to AI and how can we address them?

Leadership, as we’ve discussed, may be just as reticent to adopt an AI strategy as anyone else on the team. It’s important not to minimize or undermine their real concerns, but to address those concerns and find a solution together. Three common fears leadership has regarding AI are:

Fear of making a large financial investment without a guaranteed return.

Leaders are concerned that investing in AI may not yield results similar to past technology investments. No one wants to over-invest in technology that feels like a gamble or may not stand the test of time.

The solution to mitigate this fear is to really start small. Form a team, take small, incremental steps, build prototypes, and conduct tests before requesting significant financial commitments. This approach allows for a more measured and controlled investment.

Fear of AI becoming too powerful and taking over the business.

Leaders worry about losing control if AI becomes self-aware. While this fear may feel a bit too science fiction, there is no doubt that the rate at which AI is developing is alarming and unprecedented. Who knows where AI development will go in the future?

The solution to address this fear is to implement responsible AI frameworks and guidelines. These frameworks ensure that AI is used in a controlled and ethical manner, reducing the risk of it becoming uncontrollable.

Fear of looking uninformed or silly.

Many leaders feel overwhelmed by the complexity of AI and fear making decisions without fully understanding it. Fortunately (and unfortunately) there is a lot of noise surrounding AI and it’s hard to know what information is accurate.

To mitigate this fear, organizations should provide education and training to leaders, helping them gain a better grasp of AI concepts and applications. This knowledge empowers leaders to make informed decisions and feel more confident about AI initiatives.

Additionally, dealing with complacency among leaders, especially in large organizations, is a challenge. Overcoming complacency often requires demonstrating small successes with AI projects to gradually build trust and acceptance among leadership.

Pro Tip: We mentioned earlier that a small committee across departments might be beneficial. Think about a set of team members who can test and report on different AI applications over some time. They can then present their findings weekly to help inform the organization on usage guidelines and conduct organizational-wide training on tools they deem beneficial.

Question 4: What are Opportunities and Threats of Implementing AI in Our Organization Today?

As we discussed in our previous Strategy Collaborative session, technology disruption isn’t always negative, and AI won’t necessarily be a threat to your organization. It’s only one if you don’t capitalize on the opportunities it presents.

Which begs the question — when do we need to jump on this or risk going the way of Blockbuster?

Blockbuster had an opportunity to jump on the streaming train, and they missed it. The rest is history. So how do you prevent your business from going the same way when implementing an AI strategy? When does your business need to jump on the AI train or get left behind at the station?

TODAY. The reality is that the AI train is leaving now.

If you are not already involved with AI, your competitors likely are, and they have a head start against you. To stay competitive, research industry-specific AI offerings and what your competitors are currently using in their business processes to determine what is realistic for your organization to adopt.

At the very least, do your due diligence and create a plan. If you plan to do nothing with AI at this moment, then fair enough. But don’t just sit there and let the moment pass you by!

Fortunately, we are in a position where we get to see this unfold in real-time and benefit from the opportunities as they develop. Why would you want to miss out?

AI Opportunity use-cases

What opportunities are emerging with AI in the A&E (architecture and engineering) consulting space?

This example is very specific, but it helps demonstrate an interesting use case for the limitless ways AI can transform many professional service industries, such as architecture and engineering. Here are a few examples of opportunities or benefits that AI might provide this industry and others like it:

AI in creative workflows

Revolutionize architectural and engineering design processes by generating designs based on specified parameters and creatively merging existing structures with new structures.

AI in basic tasks

Helping automate measurements, calculation, and basic design elements, allowing consultants to focus on providing higher-level expertise.

Thinking space

Free up more time for idea generation, allowing for more rounds of creative iterations and improved quality of work.

AI has the potential to enhance consulting services by taking on more basic or mechanical tasks, allowing consultants to focus on maintaining client trust and delivering higher-value expertise.

Other use cases to consider using AI for are producing SOPs, policies, and other technical tasks that are time-consuming and mundane.

Considerations for the future: AI will impact staffing

Your staff may have fears that implementing AI into your workflow will ultimately lead to replacing them in their roles. Unfortunately, there’s no way around it. This could be a very real possibility. Ideally, when organizations begin implementing AI for remedial or mundane tasks, this will allow staff to open up their time to pursue higher-level tasks that drive business value. When approaching AI from this lens, your staff will have no reason to fear the security of their jobs. Here are two ways, as leaders, you can further minimize and resolve their fears:

Be open and honest with your team

Have a candid conversation with employees about AI and present it as a positive opportunity rather than a threat. Your employees are likely already aware of AI developments and should be included in the conversation. Honesty and transparency are important in addressing your workforce’s concerns.

Reskill and train your staff

Providing training and career development paths for employees to transition into AI-related roles is imperative. Re-skill your employees to leverage AI, even with limited funding, and take small steps to build the necessary capabilities over time. As with most shifts and changes in business processes, this may empower some of your staff to level up, and some to move aside.

Ultimately, AI provides an opportunity for anyone who desires to do so to learn and grow in their skill set. Leaning into the changes AI is bringing forward will give all staff and organizations a competitive advantage. It is only a threat to those unwilling to adapt and level up.

Question 5: What are the Challenges of AI Today?

The accuracy (or lack thereof) of generative AI models

It’s well known that human decision-making benefits from good, reliable data, which isn’t always a strength of AI models. As we continue working with AI, we have to be careful to ensure AI is providing relevant, reliable, and factual information. How can we do that?

Although the reliability of information is something that AI engineers are continuing to work on, there is still a way to go. Fortunately, there is ongoing research to understand how AI arrives at its conclusions and how to better improve the results it provides. In the meantime, we (humans) can conduct some quality assurance practices ourselves when working with any AI model.

Adopt a consensus model

While artificial intelligence isn’t perfect, neither is human intelligence! Just as we need to be fact checked, so does the AI model. Using multiple AI systems to create a consensus model, similar to consulting multiple human experts, is suggested as a way to enhance AI’s reliability and accuracy in the future. The beauty of machine learning models is that they are continually improving and getting more accurate over time.

The quality of the output correlates to the quality of the input

The power of language models, especially ChatGPT, comes from the criteria you’re providing in the question. Even changing one word will dramatically shift what it produces for you. The more you talk to it and refine your prompts, the better it learns what you’re asking for. The machine can’t interpret your intentions, so specificity and refinement are key!

How will AI affect how we deliver products and services to our customers?

One final concern that we touched on in our session is how AI solutions may potentially impact our value proposition and what we can charge for our work. While AI can take over certain tasks, it doesn’t necessarily reduce our budget. Instead, AI enables businesses to offer more for the same cost, evolving client expectations and fostering a competitive edge.

Unlocking time for higher-value work

Using AI gives us the ability to free up valuable time, allowing professionals to focus on higher-value tasks. This shift in resource allocation can ultimately benefit both clients and service providers.

For example, an advertising agency can offer distinct fee packages—one with AI involvement and one without. This approach reflects the changing landscape of professional service industries, where AI is integrated to enhance efficiency and cost-effectiveness.

Skill and expertise: The X-factor in AI implementation

While AI tools become more accessible, there is now a stronger focus on expertise in leveraging these technologies effectively. It’s not just about using AI; it’s about mastering it to achieve the best results.

Conclusion

Navigating the challenges of AI technology requires a proactive approach and staying updated on the latest advancements. By understanding and embracing AI, organizations can position themselves for success in the ever-evolving landscape of technology.

We hope that you enjoyed our latest Strategy Collaborative session and that this article provided some clarity for your most burning AI strategy questions. As always, check back in for more updates and new resources as we continue to explore how to implement AI into your strategic planning initiatives!

Current AI Resources:

Fixing the cta placement

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