Resulting IT | AI Transformation Index

Overview

Resulting IT is an independent SAP consultancy specializing in S/4HANA migration advisory, program management, and delivery services, generating revenue through fee-for-service engagements across the SAP transformation lifecycle.

Executive Summary

Resulting IT is a well-regarded boutique SAP consultancy with genuine client loyalty and a promising early AI initiative, but it sits structurally in one of the most exposed positions in professional services — an independent advisory middle layer whose core deliverables are highly automatable and whose profit pool is under pressure from both SAP itself and scale competitors with proprietary AI platforms. The AI opportunity is real and substantial, particularly for compressing the cognitive labor of Phase Zero and program management work, but that same opportunity is available to every competitor in the market and to the clients themselves — making this a race to the bottom on advisory margins unless Resulting IT can successfully productize its domain intelligence into defensible, IP-backed tooling before larger players dominate the category.

Durability Rationale

Resulting IT's durability is structurally challenged because it occupies an advisory middle layer — between the client and the SAP/SI ecosystem — without owning the system of record, the software, or the physical delivery infrastructure that would make it irreplaceable. The core advisory tasks it performs are among the most AI-automatable forms of professional services work, and the profit pool is migrating toward SAP AG itself and large SIs with proprietary AI tooling, leaving boutique independents structurally squeezed. The company's genuine client relationships and strong NPS provide near-term stickiness, but these are reputation-based moats rather than structural ones — they slow the pressure but do not eliminate it.

Opportunity Rationale

AI represents a very significant unrealized opportunity for Resulting IT precisely because almost everything the firm does is cognitive, structured, and knowledge-intensive — roadmaps, business cases, vendor evaluations, test strategies, change management playbooks are all prime LLM territory. The company is already building in this direction with S4SensAI, demonstrating that management understands the opportunity, but the self-sufficiency discount applies modestly — with only 86 employees and a moderate engineering team, the bulk of the AI transformation upside is still ahead and would benefit from structured external catalysis. The domain intelligence dimension is real but bounded: deep SAP program experience compounds meaningfully, but much of the advisory methodology is built on codifiable SAP frameworks.

Key Risks