New Accenture Research Finds that Companies with AI-Led Processes Outperform Peers
Accenture's new research, 'Reinventing Enterprise Operations with Gen AI', reveals that 74% of organizations have seen investments in generative AI and automation meet or exceed expectations. The number of companies with fully modernized, AI-led processes has nearly doubled from 9% in 2023 to 16% in 2024. These 'reinvention-ready' companies achieve 2.5x higher revenue growth, 2.4x greater productivity, and 3.3x greater success at scaling generative AI use cases compared to peers.
However, 64% of companies still struggle to change their operations, with 61% reporting their data assets are not ready for generative AI. The research highlights four key actions for advancing operations maturity: implementing centralized data governance, embracing a talent-first reinvention strategy, ensuring business and tech teams co-own reinvention, and adopting leading processes to drive business outcomes.
La nuova ricerca di Accenture, 'Reinventare le Operazioni Aziendali con l'AI Generativa', rivela che il 74% delle organizzazioni ha visto investimenti in AI generativa e automazione soddisfare o superare le aspettative. Il numero di aziende con processi completamente modernizzati e guidati dall'AI è quasi raddoppiato, passando dal 9% nel 2023 al 16% nel 2024. Queste aziende 'pronte alla reinvenzione' ottengono un crescita del fatturato superiore di 2,5 volte, una produttività maggiore di 2,4 volte e un successo maggiore di 3,3 volte nell'espandere i casi d'uso dell'AI generativa rispetto ai concorrenti.
Tuttavia, il 64% delle aziende fatica ancora a cambiare le proprie operazioni, con il 61% che riferisce che i propri asset di dati non sono pronti per l'AI generativa. La ricerca evidenzia quattro azioni chiave per avanzare nella maturità delle operazioni: implementare una governance dei dati centralizzata, abbracciare una strategia di reinvenzione focalizzata sul talento, garantire che i team di business e tecnologia condividano la responsabilità della reinvenzione, e adottare processi leader per guidare i risultati aziendali.
La nueva investigación de Accenture, 'Reinventando las Operaciones Empresariales con AI Generativa', revela que el 74% de las organizaciones ha visto que las inversiones en AI generativa y automatización cumplen o superan las expectativas. El número de empresas con procesos completamente modernizados y liderados por AI casi se ha duplicado, pasando del 9% en 2023 al 16% en 2024. Estas empresas 'listas para la reinvención' logran un crecimiento de ingresos 2.5 veces superior, una productividad 2.4 veces mayor y un éxito 3.3 veces mayor en la escalabilidad de casos de uso de AI generativa en comparación con sus pares.
No obstante, el 64% de las empresas aún lucha por cambiar sus operaciones, con un 61% informando que sus activos de datos no están listos para AI generativa. La investigación destaca cuatro acciones clave para avanzar en la madurez operativa: implementar una gobernanza de datos centralizada, adoptar una estrategia de reinvención centrada en el talento, asegurar que los equipos de negocio y tecnología compartan la responsabilidad de la reinvención, y adoptar procesos líderes para impulsar los resultados empresariales.
액센츄어의 새로운 연구, '생성적 AI로 기업 운영 혁신하기'는 74%의 조직이 생성적 AI와 자동화에 대한 투자가 기대치를 충족하거나 초과했다고 밝혔습니다. AI 중심의 완전히 현대화된 프로세스를 갖춘 기업의 수는 2023년 9%에서 2024년 16%로 거의 두 배로 증가했습니다. 이들 '혁신 준비 완료' 기업은 동료들에 비해 2.5배 높은 수익 성장률, 2.4배 높은 생산성, 3.3배 높은 생성적 AI 사용 사례 확장 성공률을 나타냅니다.
그러나 64%의 기업은 여전히 운영 변화에 어려움을 겪고 있으며, 61%는 데이터 자산이 생성적 AI에 준비되지 않았다고 보고합니다. 연구는 운영 성숙도를 향상시키기 위한 네 가지 핵심 조치를 강조합니다: 중앙 집중식 데이터 거버넌스 구현, 인재 중심의 혁신 전략 수용, 비즈니스와 기술 팀이 혁신을 공동 소유할 것을 보장, 그리고 비즈니스 결과를 추진하기 위한 선도적인 프로세스 채택.
La nouvelle recherche d'Accenture, 'Réinventer les Opérations d'Entreprise avec l'IA Générative', révèle que 74% des organisations ont vu les investissements dans l'IA générative et l'automatisation satisfaire ou dépasser les attentes. Le nombre d'entreprises disposant de processus entièrement modernisés et pilotés par l'IA a presque doublé, passant de 9% en 2023 à 16% en 2024. Ces entreprises 'prêtes à la réinvention' réalisent une croissance du chiffre d'affaires 2,5 fois supérieure, une productivité 2,4 fois plus élevée et un succès 3,3 fois plus important dans l'échelle des cas d'utilisation de l'IA générative par rapport à leurs pairs.
Cependant, 64% des entreprises ont encore du mal à changer leurs opérations, avec 61% signalant que leurs actifs de données ne sont pas prêts pour l'IA générative. La recherche met en évidence quatre actions clés pour faire progresser la maturité opérationnelle : mettre en œuvre une gouvernance des données centralisée, adopter une stratégie de réinvention axée sur le talent, garantir que les équipes commerciales et techniques partagent la responsabilité de la réinvention, et adopter des processus leaders pour orienter les résultats commerciaux.
Die neue Forschung von Accenture, 'Unternehmensoperationen mit generativer KI neu erfinden', zeigt, dass 74% der Organisationen festgestellt haben, dass Investitionen in generative KI und Automatisierung die Erwartungen erfüllen oder übertreffen. Der Anteil der Unternehmen mit vollständig modernisierten, KI-gesteuerten Prozessen hat sich nahezu verdoppelt, von 9% im Jahr 2023 auf 16% im Jahr 2024. Diese als 'reintegationsbereit' bezeichneten Unternehmen erzielen ein 2,5-mal höheres Umsatzwachstum, eine 2,4-mal höhere Produktivität und einen 3,3-mal höheren Erfolg bei der Skalierung von Anwendungsfällen für generative KI im Vergleich zu ihren Mitbewerbern.
Dennoch haben 64% der Unternehmen weiterhin Schwierigkeiten, ihre Abläufe zu verändern, wobei 61% berichten, dass ihre Datenbestände nicht bereit für generative KI sind. Die Forschung hebt vier Schlüsselmaßnahmen zur Verbesserung der operationellen Reife hervor: die Implementierung einer zentralisierten Datenverwaltung, die Annahme einer talentfokussierten Innovationsstrategie, die Gewährleistung, dass Geschäfts- und Technikteams die Verantwortung für die Innovation gemeinsam tragen, und die Einführung führender Prozesse zur Erreichung betrieblicher Ergebnisse.
- 74% of organizations report investments in generative AI and automation meeting or exceeding expectations
- 63% of companies plan to increase efforts and strengthen AI capabilities by 2026
- Number of companies with fully modernized, AI-led processes doubled from 9% to 16% in one year
- 'Reinvention-ready' companies achieve 2.5x higher revenue growth and 2.4x greater productivity
- AI-led companies have 3.3x greater success at scaling generative AI use cases
- 64% of companies struggle to change their operational methods
- 61% of companies report their data assets are not ready for generative AI
- 70% of organizations find it hard to scale projects using proprietary data
- 82% of companies at early stages of operations maturity lack a talent reinvention strategy
- 78% of executives indicate AI is advancing too fast for their organization's training efforts
Insights
The research findings from Accenture highlight significant trends in AI adoption and its impact on business performance. Key takeaways include:
- 74% of organizations report meeting or exceeding expectations from generative AI and automation investments
- 63% plan to increase AI efforts by 2026
- Companies with fully modernized, AI-led processes have nearly doubled from
9% to16% in one year - These "reinvention-ready" companies achieve 2.5x higher revenue growth and 2.4x greater productivity
However, challenges remain:
64% of companies struggle to change operations61% report data assets not ready for generative AI82% at early stages lack a talent reinvention strategy
Accenture's research reveals the transformative potential of generative AI across enterprise operations. The rapid adoption rate, with AI-led processes nearly doubling in a year, signals a paradigm shift in how businesses operate. Key technical insights include:
- Generative AI use cases are expanding beyond IT into marketing, customer service, finance and R&D
- A robust digital core is important for scaling AI initiatives
70% of companies struggle to scale projects using proprietary data- Cloud-based process mining is recommended for identifying operational inefficiencies
The emphasis on data governance and standardization is critical, as it forms the foundation for effective AI implementation. The report's recommendation to connect processes and tools across functions highlights the need for a holistic approach to AI integration. For investors, this underscores the importance of assessing a company's technological infrastructure and data strategy when evaluating its AI readiness and potential for future growth.
Investments in generative AI and automation capabilities meet or exceed expected benefits
According to the report, “Reinventing Enterprise Operations with Gen AI,” the number of companies that have fully modernized, AI-led processes has nearly doubled from
According to the report, “Reinventing Enterprise Operations with Gen AI,” the number of companies that have fully modernized, AI-led processes has nearly doubled from
Findings also assessed that these “reinvention-ready” companies are moving faster and are amplifying the impact of generative AI across the business. Enabled by a digital core, these organizations have already developed generative AI use cases in IT (
While the research indicates that some companies have moved to the highest level of operations maturity, nearly two thirds (
The deep dependency on people is often overlooked:
“Most executives understand the urgency of reinventing with generative AI, but in many cases their enterprise operations are not ready to support large scale transformation,” said Arundhati Chakraborty, group chief executive of Accenture Operations. “Generative AI is more than the technology. It is a driver of a mindset change that impacts the entire enterprise. It requires organizations to have a strong digital core, data strategy and a well-defined roadmap to change the way they operate. Additionally, an end-to-end perspective leveraging talent, leading practices and effective collaboration between business and technology teams is essential for intelligent operations.”
The report highlights four key actions business leaders should take to advance their operations maturity:
- Implement a centralized data governance and domain-centric approach to data modernization. Connect processes and tools across functions to ensure people have a clear understanding of how to create, handle and consume data, which should be structured in a standardized way to be accessed by AI tools across the business.
- Embrace a talent-first reinvention strategy. Reinvent work and rethink processes and entire workflows to gain a clear view of where generative AI can have the most impact in serving customers, supporting people and achieving business outcomes.
- Ensure business and tech teams co-own reinvention. Collaboration drives innovation as both teams jointly own how assets, platforms and products are developed to leverage the full capabilities of generative AI, enterprise wide.
- Adopt leading processes to drive business outcomes. Apply cloud-based process mining to calibrate internal and external benchmarks so it’s easier to visualize process gaps and get clear insights into operational inefficiencies or opportunities for improvement.
Explore the report in Accenture’s thought leadership app, Foresight, and get a personalized feed of recent latest insights, data, case studies and more at http://www.accenture.com/foresight.
About the Research
For the report, “Reinventing Enterprise Operations with Gen AI,” Accenture surveyed 2,000 executives across 12 countries and 15 industries. The latest research assessed the progression of business operations maturity across four criteria: Reinvention-ready, Insight-driven, Automated and Foundational —each underpinned by more advanced ways of working with data, automation, common AI and generative AI. The study then combined survey responses with externally validated data across multiple dimensions of value, including financial, experience, sustainability, talent, inclusion and diversity, innovation and agility.
The revenue growth comparison was done by leveraging financial performance data for companies in our survey (for companies with available data and after performing appropriate data quality assurance). For each intelligent operations group, Accenture looked at overall revenue in a given fiscal year and, based on this metric, calculated the group revenue growth ratio.
About Accenture
Accenture is a leading global professional services company that helps the world’s leading organizations build their digital core, optimize their operations, accelerate revenue growth and enhance services—creating tangible value at speed and scale. We are a talent- and innovation-led company with 774,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com.
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Samuela Marti
Accenture
+39 329 1595781
samuela.marti@accenture.com
Deepshikha Sinha
Accenture
+91 9599039276
deepshikha.a.sinha@accenture.com
Source: Accenture
FAQ
What percentage of organizations have seen investments in generative AI meet or exceed expectations according to Accenture's research?
How much higher revenue growth do 'reinvention-ready' companies achieve compared to peers, as per Accenture's study?
What percentage of companies plan to increase their efforts in AI capabilities by 2026, according to Accenture's report?
How has the number of companies with fully modernized, AI-led processes changed from 2023 to 2024, as per Accenture's research?
What percentage of companies struggle to change their operational methods, according to Accenture's study?
