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Byline by Chris Stephenson, alliantgroup Managing Director of Intelligent Automation & AI
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Whether we like it or not, there is incredible pressure on businesses to adopt AI. That pressure is only increasing as AI spending is expected to grow by nearly 30% over the next four years. Yet, questions remain on what and how much AI can actually do. As we head into budgeting season, this pressure leaves IT departments in every industry scratching their heads, trying to figure out how much they allocate to AI pilots. Spend too little, and the competition could develop an insurmountable advantage – spend too much, and you may find out that there isn’t enough ROI.
The reality is – AI needs a plan. With the right strategy, you can kick-start your projects by investing only a fraction of your budget. Well-executed AI initiatives have the potential to not only pay for themselves but also generate significant returns. Laying out a clear roadmap for adoption will put you ahead of the pack and position you as a leader in the AI game.
Even 1% of your budget can be done well
Let’s get this out of the way – spending more on AI doesn’t make you a leader in AI. Wedbush published a report that showed 1% of total revenue (approximately 8-10% of IT budgets) at major tech firms would be dedicated to AI. Meanwhile, a poll of CIOs revealed that 61% find it extremely challenging to prove ROI on their tech investments, with 42% not expecting positive ROI from AI projects within the next year.
Think about that for a moment – how much technology debt your IT department is already in because of projects showing no return or even negative returns. Now, you face the added pressure to bank on a new solution. The critical question is how to introduce AI within the constraints of your available budget while demonstrating ROI that drives widespread adoption and does not contribute to past failure.
The key is to start small – initiating pilot projects with a well-planned strategy rather than a comprehensive infrastructural overhaul. This approach allows your team the necessary time to transition and adapt while providing the flexibility for iterative improvements. You will have room for improvisation until you find a solution that works best for your business and see the impact in terms of revenue. By focusing on specific, manageable projects, you can gather valuable data and insights, refine your approach, and gradually scale up your AI initiatives.
How do you do it? Here are a few guiding principles that I believe will help you make the most out of your AI investment.
Conduct an ‘AI discovery’
The first step is deliberately defining and choosing your first wave of AI pilots. There are people up and down your organization with a ‘great’ AI idea. If you chase all of them, and you’ll end up with a budget you can’t justify. On the other hand, if you only focus on the ideas that the loudest voices in the room suggest (or the voice with the highest title) you’ll likely miss out on the ideas most likely to have the biggest impact.
We often start with an AI Discovery process where all ideas are put on the table and each idea is objectively scored on a 12-point rubric based on technology fit, complexity, and ROI.
During a recent AI Discovery session with a CPA firm, the tax department wanted to automate tax return preparation, while the accounts receivable team sought to streamline payment processing. The objective behind both was to save more time. However, by scoring these ideas on project scale, complexity, potential ROI, strategic alignment, and feasibility, the firm decided to prioritize the accounts receivable project.
AI Discovery not only helps in selecting the most promising AI projects but also ensures that your initial investments are targeted and effective. It allows you to focus your resources on initiatives that are most likely to deliver measurable benefits, thereby increasing the likelihood of demonstrating a positive ROI.
Plan and prioritize self-funding transformations
Once you have conducted an AI Discovery and identified the most promising pilot projects, the next step is to focus on initiatives that are lower in complexity but offer a faster turnaround in terms of ROI. By starting with these types of AI pilots, you can create a self-funding transformation process that not only justifies the initial investment but also generates the momentum needed to fund subsequent projects.
Choosing AI projects that are simpler to implement and can quickly demonstrate tangible benefits allows you to build a strong business case for further investment. These initial successes can serve as proof points, showcasing the potential of AI to drive meaningful improvements and efficiencies within your organization. For instance, automating routine tasks or enhancing customer service through AI-driven chatbots are examples of low-complexity projects that can deliver quick wins.
Consider the case of the CPA firm I mentioned. Through AI Discovery, we identified automating their accounts receivable process as an effective initial project, quickly boosting their finances. This success enabled them to automate client document requests, saving 15% in tax return preparation time (which was the initial project suggested by the tax team).
Much like the CPA firm, you can invest the revenue or cost savings generated from pilot projects into more complex and ambitious AI initiatives. This approach minimizes financial risk and ensures that each step in your AI journey is backed by demonstrated success. It also helps in gaining confidence and buy-in from stakeholders, as they can see the direct impact of AI on the organization’s bottom line.
Balancing pilot projects with comprehensive AI transformation
While focusing on launching pilot projects, you shouldn’t lose sight of the larger picture. The biggest ROI will ultimately come from company-wide AI initiatives. To achieve this, your entire organization needs to be AI-ready. This means fostering a culture that is open to innovation, investing in training and development, and ensuring that your infrastructure can support broader AI applications.
Moreover, you must keep in mind that not all pilot projects will succeed. Therefore, you should never put all your AI eggs in one basket. Diversifying your AI investments across multiple departments —such as finance, customer service, and operations— you can gather a wide range of insights that allows you to mitigate risks and identify the most impactful use cases.
Starting multiple AI pilots across departments will also accelerate your organization’s readiness for a complete AI transformation. Each successful pilot not only delivers immediate benefits but also builds the foundation for larger, more integrated AI projects. This approach ensures that your organization is continuously learning and adapting, making it more agile and better prepared for future challenges.
The true currency of AI leadership
AI has presented us with a daunting challenge, beyond which lies an unprecedented opportunity for growth and innovation. What’s evident is that success in the AI race won’t be determined by the size of your budget, but by the depth of your strategic vision. The true leaders in this space will be those who can artfully balance innovation with fiscal responsibility, leveraging small, strategic investments to catalyze transformative change. In this new paradigm, the most successful companies won’t just adopt AI – they’ll redefine how AI adoption itself is approached, setting new standards for efficiency, creativity, and return on investment in the process.
While your CTO and CIO are crucial players, the data you need to make the highest impact often sits with another executive: your Chief Human Resources Officer (CHRO).
While your CTO and CIO are crucial players, the data you need to make the highest impact often sits with another executive: your Chief Human Resources Officer (CHRO).
Here’s why your CHRO could be the secret weapon as you go through the AI discovery process:
- Who better understands your workforce’s skills, challenges, and potential than HR? They’re the keepers of your company’s human capital knowledge, data that is necessary to analyze the impact of potential solutions.
- HR understands your hiring struggles, pinpointing exactly where your organization needs an augmented workforce.
- They know why people stay, and more importantly, why they leave. This insight is key when prioritizing & designing potential AI solutions.
Your CHRO is a critical bridge between your tech ambitions and your most powerful asset: your people. Through their data and insights, your organization can better understand where the current workforce most needs assistance, redefine job roles to better align with AI solutions, and ultimately knows where AI fits best.
Being the AI compass
When crafting your digital roadmap, your HR team needs to a part of the conversation. From hiring, talent and change management, and determining points ripe for automation, here are some key areas where your HR department can help you with your AI implementation.
- Identify where your company is struggling to hire. Your HR department can analyze job postings and hiring data, pinpointing bottlenecks in your recruitment process. Jobs that are difficult to hire for or retain are great places to start with AI.
- Ascertain skills that are needed in each department. Your HR team can determine the skill requirements of each department based on successful hires and current employees.
- Assess repeatable activities common across the organization. HR understands the details of each job role and can best identify common activities that would broadly benefit from AI augmentation.
- Evaluate which departments to automate first based on need. Using this framework and their knowledge of hiring issues, HR can suggest which departments would benefit from AI tools, and in what order these implementations should take place.
Determining implementation priorities
Imagine this scenario: Your marketing team wants a chatbot, accounting needs an AP/AR automation tool, and sales is really excited about automating the proposal and contracting process. You HR team has the data to objectively prioritize these three options. They know that accounting has the highest turnover due to tedious data reconciliation tasks. Armed with this insight, they can make a data-driven case for prioritizing the accounting department’s AI needs, potentially solving multiple problems with one strategic move.
Alternatively, all three departments are short staffed, and based on the open job postings, every department could benefit from some form of data entry as opposed to a specialized tool for each department. Your HR department can then recommend that automation of data entry would benefit all departments, making it the correct route through which to start your digital journey. Each walks away with a tangible benefit to their team, allowing them to focus on addressing these issues internally instead of spending resources on data entry.
While your CTO and CIO are the critical players in implementing successful AI solutions, prioritization is one arena where your HR team’s insights can result in the most positive change. From a tech standpoint, every team is going to have certain needs, and it might be harder for other roles to consider the employee’s opinion on where this can have the most impact. Your CHRO can be a key asset in deciding where to focus your efforts first.
Empowering the unsung hero of your organization
While balancing organizational goals with employee requests can be a tight rope to walk, having the internal knowledge of how departments are performing, as well as who could truly benefit most from an AI tool, makes HR a key decision maker in this process.
So, when you are going through your journey of AI discovery, make sure your HR department is part of that team. The insights they bring can greatly increase the speed and impact Generative AI can create at your organization.
Featured Leadership
Dhaval Jadav is Chief Executive Officer of alliantgroup, America’s leading consulting and management engineering firm, which helps American businesses overcome the challenges of today to prepare them for the world of the 22nd Century and beyond. Jadav co-founded the firm in 2002 to be unlike any other consultancy, with an emphasis on partnerships with clients to not only identify but also implement quantifiable solutions to their most critical concerns.
Chris Stephenson is Managing Director of Intelligent Automation & AI at alliantgroup and was previously a Managing Principal at Grant Thornton.
