Carl Seidman is a trusted business advisor specializing in financial planning and analysis (FP&A), business strategy, and finance transformation. He coaches and advises FP&A professionals at Fortune 500 corporations and middle-market companies, helping establish best practices, processes and sustainable business models. At the same time, Carl brings finance professionals greater control over their careers by helping them build their skills while eliminating time-wasting activities and mistakes.
So much of the chatter right now is about AI changing what analysts do. But as I mentioned in a previous series of The Statement, I actually believe AI is going to eliminate a significant portion of what analysts are hired for in the first place.
There is a widespread belief in this space that AI is going to kill Excel. I want to be direct: I think that’s wrong. I get prodded on this regularly on LinkedIn, where salespeople who work at software companies tell me that Excel can’t scale.
This issue shifts to the market that many finance professionals have turned to instead: online courses, training platforms, and self-paced learning. The outlook here is not much better. In some ways it’s more precarious. I hope my rationale explains why I take the position that I am.
I teach data analytics at the graduate level and I genuinely love that work. So before I go further, let me be clear: I am not anti-college. I am anti-autopilot. And the autopilot assumption — that a four-year degree is the default next step for almost every young person…
In recent editions of The Statement newsletter, I’ve shared how I believe the structure of management consulting, public accounting, and investment banking firms is about to change dramatically. Most notably, it’s going to upend the status quo of billable hours (shifting instead to value-based billing).
Effective finance operations are often seamless and unobtrusive. Data flows efficiently, models update automatically, cash timing is predictable, and leaders receive timely, reliable answers. When finance processes break down, inefficiencies become apparent throughout the organization.
When I go into a new client and am tasked with putting together cash flow projections or rolling forecasts, one of the most material elements is capital expenditures (capex). Capex is obviously more than hard-coded spreadsheet entries in Excel.
At least once a week – when talking with people about AI, finance, and jobs – the conversation often goes back to this single question: “What’s going to be the impact of AI on accounting and finance professionals?
When I was in college, there were three business careers that deeply intrigued many accounting and finance students. They promised the ideal combination of being in demand, lucrative, and secure.
About six months ago, a Principal at an SF Bay Area venture capital firm reached out to me and proposed. Not nuptially. He wanted to buy my financial models. I was taken aback by the offer. I had never received that kind of request before. Naturally, I asked a few questions.