Too Many Finance Teams Lack Will And Skill AI Wave Demands
Boards have a quiet, growing crisis — understaffed and underskilled finance functions now struggle to meet routine stewardship responsibilities, leaving insufficient resources for digital strategy acceleration and business support.
What’s worse is that most CFOs know it and have little appetite for change.
A survey of over 1,000 financial executives, EY’s 2023 DNA of the CFO Report, found that while 16% of respondents rate their finance function as “best-in-class,” only 14% plan to “pursue a bold transformation agenda in the next three years.”
History suggests that few CFOs truly have the fortitude, time, incentives and trusted tech partnerships to orchestrate grand-scale finance function modernizations. For decades, growth fantasia peddlers or myopic penny-pinchers left enterprises burdened with outdated manual processes, bootstrapped budgets, cash-draining legacy projects, recurring performance gaps — and large personal payouts.
Faced with that harsh reality, boards must demonstrate the courage and candor to acknowledge, assess and address finance function readiness for an AI push that will definitively either elevate or expose executives’ competency. For leaders, AI elevates strategic influence, tightens controls, enhances business agility and betters results. For “leaders-in-title-only” (LITOs), bungled AI initiatives will spotlight data disarray, flawed staff skill, lax oversight and broken cross-functional relationships.
Diamonds and rust
CFOs are under enormous pressure to navigate digital era competition, unrelenting cyberthreats, cost uncertainty, shifting employee expectations and emerging financial reporting complexities. The cracks are starting to show.
Research firm Bedrock AI astonishingly found that almost 600 U.S.-listed companies disclosed material internal control weaknesses arising from accounting and IT personnel needs. The deficiencies are likely far more pervasive and pernicious than the self-reports. For instance, retailer Advanced Auto Parts recently late-filed its quarterly financials due to “loss of certain accounting personnel and turnover of accounting positions.” That’s a major avoidable misstep by a public company.
There’s little relief ahead. The “great accountant shortage” is growing as mass retirement and job resignation trends are compounded by shallow technical talent pools. Over 300,000 U.S. accountants and auditors left their jobs after the pandemic. The majority of CPAs are at or near retirement age, college accounting enrollments are swooning and audit and tax firms are severely understaffed.
That’s a big AI appeal – automate what people cannot or will not sufficiently do.
Yet, generative AI implementation challenges can’t be overstated. Far more than “an IT project,” they require sophisticated change management, strong oversight and culture-shaping leadership. If asked about generative AI’s purpose, potential and usage, real leaders answer with definitive clarity and compelling evidence. Conversely, “LITOs” tailspin with buzzword responses, distracting and off-point anecdotes, blame-shifting desperation and lip-service follow-through.
Well-staffed finance teams contribute meaningfully to business aims, maintain tight control and meet compliance standards. Underperformers are distrusted in the workplace, offer little business insight, impede strategic competitiveness and hamper operational excellence. The latter is no match for digital era complexity.
Boards simply cannot risk company futures in the wrong hands. Finance functions are already behind and executives sense it. Nearly 72% of the EY respondents blamed “traditional back-office behaviors and mindsets” for “slowing the modernization of the function.” That’s severely ill-fitting for the lasting change AI brings.
To assess finance AI’s success odds, boards should start with three bold diagnostics.
1. Will generative AI implementation primarily serve transactional or transformational priorities? Deloitte reported that many traditional transaction finance activities such as “billing, payments, and collections will be largely automated through AI. Variance analysis and scenario analysis will be easily produced in the format the user prefers.”
Further, Deloitte recognized from a controllership view, while, “CFOs are not likely to trust AI to produce regulatory financial filings anytime soon. However, creating reliable drafts for internal reporting and parts of external financial reporting, such as earnings releases using GenAI, could save significant time during [period] closes.”
Finance teams whose answers are limited to a compliance and reporting focus likely lack the foresight to convincingly identify or leverage AI’s strategic business value. Their prioritization will be highly revealing and predictive of the eventual implementation’s vision, scope, depth and usage.
Without great specificity, the chances that generative AI will improve strategic decision making, resource decisions and business performance plummet.
2. Who are the trusted partners to design, implement and utilize AI investment? Name names. Who has the credible experience to successfully lead and oversee grand-scale tech initiatives? Are there IT partners who truly understand enough about financial reporting and possess sufficient business acumen to best fit the enterprise’s future needs?
Candidly, which current jobs are in jeopardy? Employees naturally reject insincere claims that tech aids jobs and doesn’t replace them. Jobs that can be automated will. Not surprisingly, many legacy accounting and auditing jobs score high risk of obsolescence (71%).
As such, senior leaders team must seriously question why routine tasks were not automated long ago. Does such delay and risk bode well for the AI adoption’s business transformation? Far beyond technical and technological skill, does the team have the persistence, perseverance and tolerance for the demands of organizational, culture and work flow change? An honest talent critique yields those answers.
3. How will generative AI tools speed and boost business resilience? In addition to planning, control and review, AI tools enable organizations to be responsive. For instance, the SEC’s new cybersecurity regulations require attack assessment and disclosure within four days. Such alacrity assumes a fundamental understanding of business disruptions’ financial statement effects. Those judgments rest upon how well and how swiftly cross-functional teams can triage and thwart cyberthreats and mitigate reputational, operational and financial detriment. That skill, will and steely composure, particularly under pressure, call for special talent, tested experience and a candor culture.
The collective responses (or lack of) will reveal or conceal much a board needs to know before attempting a wildly expensive finance function AI rollout.
Wishful optimism, cheerleading platitudes and external excuse-making are no substitutes for compelling foresight, sharp stewardship and real accountability — especially and inevitably more so in the AI era.
Who’s courageously forging the future or dangerously entrenched in the past?