AI Best Practices for Management Accountants

May $13,2024$

By: Kristine M$.$ Brands, D$.$M$.,$ CMA; Mark Holtzblatt, Ph$.$D$.,$ CPA

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Nine ways management accountants can support AI deployment.

AI was a major theme at the January $2024$ World Economic Forum in Davos, Switzerland. World leaders wrestled with its potential impact on society and global economies. As OpenAI CEO Sam Altman said, $$AI has been somewhat demystified because people really use it now. And that$$s always the best way to pull the world forward with a new technology.$$ The expansion and evolution of AI is so rapid that organizations can$$t afford to blink. So as companies increasingly turn to AI$,$ staying on top of technology helps ensure they reap the benefits$$and will be able to navigate the latest challenges. Because AI$-$driven management accounting applications can create enormous value for companies, management accountants are uniquely positioned to support their organization$$s AI initiatives.

So$,$ let$$s explore nine best practices that management accountants can support to provide their organizations with a competitive advantage from AI$.$

$1.$ Choose Strategy

AI deployment requires a strategy that aligns with an organization$$s business or mission. A Deloitte report recommends that a company should develop an enterprise strategy and make dynamic adjustments to accommodate changes in market and technology conditions. Organizations following that approach are more likely to achieve AI transformation$$and that$$s helping companies turbo$-$charge their wider digital transformation.

Another must$-$have factor? AI support from top leadership that seeds proactive decision making. Deloitte points out that in $2010$ Amazon president Jeff Bezos directed company leaders to plan how they would adopt AI and machine learning to achieve a competitive advantage. And the market showed how that was a winning strategy. Management accountants can play a key role in developing performance management systems and key performance indicators $($KPIs$)$ to measure and track performance against their organization$$s AI strategy.

$2.$ Assess Risk

The AI risk level is soaring because of underlying complexities. Organizations must continuously monitor, assess, and mitigate AI risks. This includes understanding AI risks. Table $1$ explains these risks and what actions can be taken to address them.

Table $1$: AI Risks and Mitigation Recommendations

AI Risks

Description

Recommendation

AI and machine learning $($ML$)$ complexity

AI and ML are software algorithms that mimic the human brain.

Monitor, document, and control AI and ML algorithm development.

Lack of transparency

Complex mathematics and autonomous ML can handicap human understanding of algorithms.

Ensure the purpose and application of AI programs are fully disclosed, understandable to humans, and audited.

Trust issues

Teams need confidence that underlying AI technology is accurate.

Document that applications are supported with clear instructions, remove any bias, and choose the right data sets.

Algorithmic bias

AI engineers might unintentionally program bias into algorithms.

Implement a rigorous design review and testing controls to detect and eliminate bias.

Algorithmic drift and hallucination

AI might reach imperfect conclusions caused by calculating spurious or nonexistent patterns.

Audit the algorithms and the output.

Automation job loss

AI$-$generated automation is predicted to result in job loss.

Develop an upskilling$/$reskilling program $($see $$Manage Talent$$ below$).$

Hacker vulnerability

There$$s a high risk of cyberattacks and data theft because hackers will try and use AI to penetrate organizations.

Defend data with AI detection and invest in cybersecurity defenses.

Rise of techno elite

AI complexity might put disproportionate power in the hands of tech$-$savvy workers who might misuse their knowledge.

Create a culture of AI ethical values while strictly monitoring AI development.

AI isn$$t perfect. As such, it can introduce inaccurate information. That$$s why management accountants need to adopt a healthy skepticism when evaluating results. There$$s also a growing risk of misuse, abuse, and data theft calling for more diligence to safeguard data. And perhaps the biggest risk of all is addressed in the sign on Sam Altman$$s desk: $$No$-$one knows what happens next.$$ To defend against unknown risk requires companies to monitor AI developments and a willingness to change course if necessary.

$3.$ Follow Regulations

Emerging regulations will also impact how companies deploy AI$.$ Even if your country hasn$$t passed legislation, it$$s important to follow global trends and be ready when and if local regulations take effect. The European Union $($EU$)$ took the global l