Your lender is already scoring your AI strategy
43.6% saw gains reach margins, but 34.0% saw them absorbed by workload and complexity, and 26.4% offset by rising costs elsewhere. Checking is the cost nobody budgeted for. The firms that industrialise assurance, meaning error budgets, sampling rather than universal review, and audit trails robust enough for a regulator, will be the only ones able to remove the human check and keep the gain. The unit of competition moves from task to operating model. Choosing between platforms concerns 33.2% of leaders today and will concern almost nobody by 2030, as capability converges and switching costs fall. A harder question replaces it: what proportion of your work runs from end to end without a human in the loop, and what error rate will you accept in exchange? Assisted tasks build no compounding advantage, because the same assistance is available to everyone at the same price. Capital reprices before the market does. 78.1% of lenders already treat AI readiness as a significant or moderately important credit factor, and 96.8% either see the gap between stronger and weaker businesses widening or expect it to. The sequence runs from informal question, to diligence heading, to information requirement, to facility term, and each step is invisible from inside until a refinancing or a sale, when it arrives as a price rather than a conversation. Only 47.4% of lenders say borrowers consistently evidence claimed AI efficiencies in forecasts, margins or cash flow. That evidence is missing because most management teams do not realise it is being read.
Andy Pardoe Founder & Chief AI Officer at KARRIK
Background Two findings in this research sit directly opposite one another, and the gap between them is where the next five years will be decided. Ask mid-market leaders which AI issues most challenge their strategic and investment decisions, and scenario planning for under delivery comes last, at 15.2%. Ask where external advice would be most valuable, and lender and stakeholder conversations come last again, at 20.8%. Now ask the people lending them money. A third (33.5%) name the absence of credible scenario planning as a reason to send a borrower for outside help, and 45.4% say weak AI readiness could affect the pricing and margin on their lending. Management ranks these issues last; capital ranks them close to first. AI performance will show up in the cost of capital before it reaches the profit and loss account, and most boards are watching the wrong one. Three forces that will shape the next three to five years Verification becomes the binding constraint. 42.0% of organisations are increasing oversight of AI-enabled work; only 20.0% are reducing headcount. That is a supervision story, not an automation one, and it explains where the efficiency went.
12
Made with FlippingBook - professional solution for displaying marketing and sales documents online