23 Daily — According to entrepreneur.com, an expert has proposed a 90-day plan enabling companies to become AI-native without new software investments. This approach suits entrepreneurs with limited budgets by reshaping one revenue-related process and redefining workflow, data management, and decision-making practices within a single quarter.

Mapping Actual Workflows to Redefine Data and Decision Ownership

A June 2023 survey by Genpact and HFS Research of over 2,000 senior executives found that 85% of enterprises are hindered in realizing AI's value due to accumulated enterprise debt—undocumented processes, unusable data, aging systems, and unprepared personnel—estimated at around

8 trillion across the Global 2000. Only 33% of enterprise data is AI-ready, and inefficient or manual tasks consume approximately 40% of a typical employee's workweek, with more than half lacking funded initiatives to address these issues.

The plan advises startups to select one revenue-impacting process (such as quote to cash, customer onboarding, or returns) and work closely with the people running it to document its actual flow, including unofficial spreadsheets, stuck approvals, and verbal exceptions. Then, each step is classified as either 'production'—data gathering and summarizing suited to automation—or 'judgment'—decision-making requiring human oversight.

Clarifying Data Ownership and Business Metrics

After finalizing the process map, the next step is to trace information sources for each step, assigning unique owners and definitions for critical data fields like customer, product, price, status, and date. This prevents wasted effort in realigning data meaning across the enterprise.

Additionally, the plan recommends verifying that all paid tools allow complete and timely data export; if not, their contracts should be renegotiated to avoid 'renting' data. Judgment steps receive clear definitions of expected outcomes and pre-customer human review rules. Obsolete approval chains are examined for elimination. Traditional tool-centric metrics are replaced with business-focused ones—cycle time, cost to serve, and customer turnaround—measured at day 61 and day 90 to assess actual improvement.

Editor's take: A Practical AI-Native Transition for Budget-Constrained Startups

This 90-day plan highlights process redesign and data ownership as critical to becoming AI-native rather than investing heavily in software. By intervening before habits solidify, startups can reduce transformation costs and grow sustainably. The method emphasizes focusing on one high-impact process, thoroughly documenting it, managing data governance, and measuring business impact rather than tool usage.

To validate the plan's effectiveness, startups can ask if 10 new hires could onboard and understand core workflows by the next day. A positive answer signals success in operationalizing the transformation and enabling AI integration. Conversely, difficulties indicate areas needing further improvement. This approach offers entrepreneurs a pragmatic path to AI localization with minimal budget while providing concrete criteria to evaluate progress.