Artificial Intelligence: CEO Strategies and Return on Investment
Artificial intelligence is the key word in CEO strategies until 2026. Artificial intelligence is driving budget decisions, innovation, and business model redesign in large global companies.
In recent years, corporate executives have significantly increased their investments in AI, often before they even have clear visibility into the financial return. While use cases are multiplying, the gap between strategic ambition and measurable ROI remains a key challenge for the next two years.
Most CEOs view AI as a key enabler for automation, reducing operating costs, and opening new revenue streams. At the same time, stakeholder pressure demands tangible evidence of the value generated, going beyond mere technological hype.
Artificial Intelligence and CEO Priorities Until 2026
International surveys show that over 701% of CEOs plan to increase their budget for innovation projects. artificial intelligence by 2026. This trend particularly affects sectors such as financial services, retail, telecommunications, healthcare, and advanced manufacturing.
Declared priorities include intelligent automation of back-office processes, supply chain optimization, predictive demand analysis, and improved customer experience. Many leaders consider AI an indispensable lever for remaining competitive in increasingly data-driven markets.
According to estimates released by international analysts and research, the artificial intelligence It could contribute trillions of dollars to global GDP by 2030, thanks to productivity gains and new business opportunities. This potential is pushing CEOs to move quickly, even accepting a certain level of risk on the most innovative projects.
Many organizations are creating dedicated AI task forces, often directly reporting to the CEO and CFO offices, to ensure initiatives are aligned with strategic objectives and financial KPIs. AI governance is thus becoming a top-level issue, not just in IT.
From Experimentation to ROI: Measuring the Value of Artificial Intelligence
One of the main issues concerns the measurement of the return on investment related to projects. artificial intelligence. Many companies have accumulated pilot initiatives, often limited to single departments, without a clear framework of shared KPIs at the corporate level.
Moving from the experimental phase to scaled adoption requires precise metrics: reduced process times, fewer errors, increased revenue per channel, increased average customer value, and improved conversion rates. Without these indicators, it becomes difficult to demonstrate the true economic impact.
A common obstacle is the fragmentation of corporate data. Legacy systems, information silos, and a lack of standardization slow down projects. artificial intelligence and reduce their effectiveness. The most advanced CEOs are therefore promoting data modernization and platform integration programs.
At the same time, there is growing attention to risk measurement: operational, reputational, and regulatory risk. AI governance frameworks increasingly include controls, audits, and documentation, in line with the recommendations of international bodies and institutions such as the European Commission and the guidelines on responsible AI.
Skills, culture, and infrastructure to scale artificial intelligence
To transform the artificial intelligence To achieve a real competitive advantage, it's not enough to implement algorithms or purchase new platforms. CEOs must address three fundamental dimensions: skills, organizational culture, and technological infrastructure.
On the skills front, the shortage of data scientists, machine learning engineers, and AI product managers remains severe. Many companies are investing in staff reskilling and upskilling programs, complementing in-house training with collaborations with universities and research centers, as suggested by sources such as Wikipedia on Artificial Intelligence for the historical and conceptual framework.
Culturally, CEOs must promote a data-driven vision, where decisions are based not only on intuition but on structured data analysis. This implies transparency, information sharing between departments, and incentives linked to the effective use of data analysis tools. artificial intelligence.
Finally, technological infrastructure plays a critical role. The adoption of cloud architectures, data lakes, and API integration platforms allows for the connection of heterogeneous systems and the deployment of AI models at scale in areas such as customer care, logistics, and digital marketing. In this context, AI-powered vertical solutions dedicated to specific channels, such as WhatsApp Business, are also growing.
Generative Artificial Intelligence, Risks and Regulation
The spread of the’artificial intelligence Generative technology has further accelerated CEO interest. Tools capable of generating text, images, code, and multimedia content are opening up new possibilities for marketing, customer service, product development, and training.
However, these advances bring new challenges: protecting intellectual property, content quality and veracity, managing model bias, and protecting sensitive data. Corporate leaders must ensure compliance with increasingly stringent regulations, such as the European AI Act and privacy guidelines.
For many companies, the critical point is not whether or not to adopt the artificial intelligence, but how to do it responsibly, traceably, and verifiably. Governance, audit trails, and internal control systems therefore become an integral part of every AI project, especially in regulated sectors.
The most advanced organizations are establishing AI ethics committees, updating internal codes of conduct, and introducing guidelines for employees' use of generative tools. The goal is to balance innovation and risk, maintaining the trust of customers, partners, and regulators.
Artificial Intelligence: Impact on Marketing and Business
THE'artificial intelligence It has a direct and profound impact on digital marketing and companies' business models. On the marketing front, AI allows for much more precise audience segmentation, personalized messages and offers, real-time optimization of campaigns, and prediction of future customer behavior.
The integration of recommendation algorithms, predictive scoring, and behavioral analytics increases lifetime value and reduces acquisition costs. In contact centers and messaging channels, chatbots and virtual agents based on artificial intelligence improve the customer experience by offering 24/7 support and consistent responses.
From a business perspective, AI supports the definition of new dynamic pricing models, the identification of market niches, and the creation of data-driven products and services. Sales and marketing departments can quickly test new value propositions, measuring their effectiveness with integrated dashboards.
In conversational channels like WhatsApp Business, the’artificial intelligence It allows you to orchestrate automated campaigns, intelligent follow-ups, and personalized nurturing workflows. This translates into more sales, fewer cart abandonments, and a more continuous relationship with customers, which is crucial in both B2C and B2B markets.
How SendApp Can Help with Artificial Intelligence
To transform the’artificial intelligence To achieve tangible results on the WhatsApp Business channel, companies need specialized, integrated platforms that comply with official policies. SendApp was created with this very goal: to bring automation, AI, and conversational orchestration within the reach of marketing, sales, and customer service teams.
Thanks to SendApp Official, businesses can use the official WhatsApp API to connect CRM systems, ERPs and marketing automation platforms, enabling advanced flows supported by artificial intelligence. This includes transactional notifications, remarketing campaigns, personalized updates, and intelligent chatbots.
With SendApp Agent, teams can collaboratively manage all WhatsApp conversations on a single interface, combining AI automations (auto-replies, reply suggestions, intelligent routing) with human intervention at key moments.’artificial intelligence he thus becomes an operational assistant, not a replacement for the team.
SendApp Cloud It allows you to automate campaigns, follow-up sequences, segmented sendings, and multi-channel workflows, integrating data analysis and advanced reporting tools. This allows CMOs and digital managers to precisely measure the ROI of every AI initiative on WhatsApp Business.
For companies looking for a solution that can be installed locally, SendApp Desktop is also available, described on the official website SendApp, ideal for small teams who want to start leveraging automation and artificial intelligence gradually.
By integrating AI, data, and the WhatsApp channel into a single ecosystem, SendApp helps CEOs, CMOs, and customer experience managers transform their strategy into measurable results: more qualified leads, happier customers, and more efficient processes. For those who want to plan the next step, you can request a personalized consultation on the WhatsApp Business channel and activate a free trial of SendApp solutions.
Insights and guidance on the evolution of AI globally are also available through reports and analyses published by entities such as McKinsey – State of AI, which confirm the central role of the artificial intelligence in CEO strategies through 2026 and beyond.
