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Byline by Chris Stephenson, alliantgroup Managing Director of Intelligent Automation & AI
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With deals and cross-departmental alignment at year’s end, starting AI discovery in Q4 is essential for organizations looking to adopt AI.
As another year comes to a close, your business is likely strategizing and planning for next year’s opportunities. If these conversations do not already include planning an AI implementation for your business, you will be missing out on a golden opportunity to get a head start on the competition.
Why is Q4 the Most Economical Time to Adopt AI?
Once your business has set its sights on the right applications for AI, the next step is figuring out when to slot in implementation amidst all other priorities.
Depending on what industry you operate in, your busiest times may revolve around certain seasons, holidays, or school deadlines – however, most companies use the last quarter of the year to wind down, take stock, and plan for the coming year. Manufacturing operations slow down or even stop. Projections and budgeting are fleshed out.
Thus, the optimum time to get started on AI implementation is in the last quarter of the year. That means right now. This isn’t just because of operational lulls. Several other compelling factors play into the timing:
The AI Cost Landscape
The AI honeymoon we’ve enjoyed over the last few years is fading. Many are discovering that Generative AI, which is trained on datasets and used to generate text, images, or video, is so resource-intensive that many of its providers are operating at a loss. Secondary impacts such as server farm water usage and heat generation are coming to the forefront.
By the end of the fiscal year, a business will already have an idea of its AI budget. Short-term pricing will already be a known quantity. Given the uncertainty in where costs may go, it behooves businesses to lock in current pricing, which will likely be favorable compared to that in Q1 of next year, to ensure that AI implementations don’t go over budget.
Departmental Collaboration
Throughout the year, IT, Finance, Operations, and Sales chug along and meet when necessary; however, during the last quarter of the year, they’re ideally more aligned in purpose, figuring out what the next year will look like. Since the most successful AI implementations function across departmental lines, businesses should capitalize on this unity of vision. By understanding every department’s needs, decision makers can view projects holistically.
Year-End Pricing
Technology vendors have revenue goals of their own to meet. Thus, Q4 gives businesses a chance to not only take advantage of discounts, but also actively negotiate. By making sure to include future costs and potential overruns in mind, this provides a powerful opportunity for businesses looking to modernize. However, this is also a critical time to tie goals to expenditures. With most of the year behind them, decision makers know where they landed with their initiatives, versus where they wanted to be.
How Do I Get Started?
At this point you’re hopefully raring to go or at least wondering where to start. The first step in any AI implementation is a Discovery Session, during which the following is accomplished:
- Ideation – stakeholders discuss operational challenges and perceived solutions. It is critical to include representatives from all departments, and not just IT and/or finance.
- Prioritization – decision-makers rank every initiative brought to the table by importance, taking into account potential impact as well as overall urgency.
- Infrastructure Assessment – the processes, data, and infrastructure of the business are assessed for their readiness to take on proposed initiatives.
- Roadmap – participants develop implementation timeframes and milestones.
Discovery Sessions are a critical step in any company’s AI roadmap. Not only are they instrumental in the context of AI, but they are also a great opportunity for internal soul-searching. In fact, as a springboard for some potentially expansive projects, they raise some very salient questions:
Is the Desired Implementation Self-Funding?
Your business’s AI implementation should always aim to be a self-funding transformation. In other words, the cost of the technology plus the internal lift to implement it should not exceed the time and expense it ultimately saves. The net gain from the implementation can then be placed into further, bigger initiatives. Rinse, and repeat.
A recent CPA client provides a wonderful example. The firm was struggling with a manual and inconsistent process for collecting outstanding accounts receivable. By better tracking outstanding bills, standardizing the look and feel of outreach, and cleaning up data from undeliverable emails, the CPA firm collected enough in the first three hours to pay for the implementation, while significantly reducing the time that partners spent on collections.
This strategy resonates not only from a P&L standpoint, but from the aspect of starting with a smaller and simpler implementation that allows a business to work out any kinks before embarking on larger projects. In fact, the last few years’ explosion in AI usage has shown that, in many cases, it’s more effective to break a desired operation down into a series of small automations as opposed to asking AI to figure out a process all in one bite.
Are We Fully Utilizing our Tech Stack?
I have seen countless businesses who have invested in sophisticated systems such as Salesforce and then only used half of their available features. Given the complexity of today’s business software solutions, this isn’t very surprising. However, a full investigation of available functionality almost always uncovers opportunities for automations or data analysis.
Discovery Sessions offer the perfect opportunity to cut through the noise and reveal that, sometimes, a simple solution is already available in place of a desired AI implementation. Business owners just need to take the time to find it, and that time is Q4.
The Bottom Line
The AI Discovery process is not only essential before starting an implementation, it also forces a business to brutally and honestly assess its current technologies and processes. But it’s most effective when it is done during the right time of the year, which for most businesses will be right now.
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.
