In an environment of accelerating technological cycles and market turbulence, this paper substantiates the integration of entrepreneurial structures (startups, corporate venture units, spin-offs, alliances) as a key strategy for enhancing long-term corporate resilience, while highlighting the risks of cultural incompatibility and declining innovativeness under excessive bureaucratization. The purpose of the study is to systematize integration models and develop a methodology for assessing their impact on financial and operational stability. The empirical base includes 120 companies from the USA, EU, and Asia-Pacific (2015-2023), with analysis of public financial statements under IFRS/US GAAP and a retrospective spanning from three years before the event to five years after; the study employs systemic and comparative approaches, correlation-regression analysis, financial modeling, and case studies. It is shown that integration increases average EBITDA profitability by 2-5 percentage points, with the greatest effect in IT (+5.43 p.p.) and pharmaceuticals (+4.22 p.p.), moderate in the consumer sector (+2.58 p.p.), and minimal in industry (+1.16 p.p.), where effects appear with a lag. ROIIC dynamics vary by model: acquisitions show a negative first year (-2,78%) and a peak by the fifth (16,42%); corporate venture capital demonstrates a steadily positive but lower trajectory (5,12% → 12,03%); strategic alliances have the smallest effect, while internal incubators reach 14,88% by the fifth year. The maximum overall synergy is achieved with moderate autonomy of the integrated unit within the holding (1.230), balancing financial flexibility and operational coordination. High autonomy enhances financial synergy (1.31) but limits operational (1.08), while low autonomy does the reverse (1.35 and 1.05), reducing the overall effect. The relationship between RandD spending and product launch speed is nonlinear, with an effective corridor of 3,1-7,0% of revenue (strongest negative correlation with T2M), showing diminishing returns above 12%. The findings confirm that there is no universally optimal model; the managerial priority is the controlled independence of the unit, optimization of the innovation budget, and consideration of industry specifics. Limitations concern the mixing of external factors and the need to expand panel data.