Major corporations in the software industry leverage artificial intelligence to eliminate discounts and strengthen their client ties
In the rapidly evolving world of technology, the next major software decision for enterprises is a significant one. The bet is on a single vendor's security posture, pricing model, and innovation capacity for the next decade.
According to Forrester, the barrier to adopting AI is less about the AI's intelligence and more about the organizational effort required to retrain workforces on new workflows. This shift towards AI-driven enterprise software is not without its advantages.
Major enterprise application vendors are leveraging AI products, such as generative AI (GenAI) and agentic AI, to increase revenue and strategic control. By enhancing customer experience, automating operations, and enabling real-time decision-making across sales, marketing, and supply chain processes, these vendors aim to create a scalable architecture capable of horizontal scaling and effective customer intelligence monetization.
Specifically, AI is being deployed to drive personalized product recommendations and marketing campaigns, optimize margins through dynamic pricing and flash sales automation, develop proprietary AI models, automate routine tasks, and integrate AI across CRM, marketing, inventory, and supply chain systems. These strategies lead to measurable revenue increases and operational efficiency gains.
However, adopting such a strategy comes with potential risks and challenges. For tech buyers, the exposure of proprietary or sensitive data, AI biases or hallucinations, the complexity of integrating AI tools into existing legacy systems, the need for responsible AI governance, and balancing initial investments and proving measurable business outcomes are all concerns that must be addressed.
Moreover, the era of experimentation is over, and the era of monetization has begun, as noted by Forrester. Vendors are ending discounting and pushing high-margin AI products, rebundling their products to encourage customers to view their collection as a "platform of platforms." This bundling process is standard among enterprise software vendors of SAP's scale.
In 2020, SAP's then CFO Luka Mucic stated that the company was shifting from a supplier of on-prem enterprise applications to a suite of SaaS and cloud services, aiming to increase customer lifetime revenue with the subscription model and expand their share of the wallet.
In summary, enterprises stand to gain revenue growth and competitive control by embedding AI-driven personalization, automation, and intelligent decision-making into their applications and operations. Tech buyers, however, must carefully navigate data privacy, integration, ethical governance, and measurable ROI challenges associated with AI adoption. The study included Oracle, SAP, Workday, Microsoft, ServiceNow, and Salesforce.
- In the evolving tech landscape, artificial-intelligence (AI) is being employed by major enterprise application vendors to boost revenue and strategic control.
- AI is used to enhance customer experience, automate operations, and enable real-time decision-making, aiming to create a scalable architecture in sales, marketing, and supply chain processes.
- By driving personalized product recommendations, optimizing margins through dynamic pricing, and integrating AI across CRM, marketing, inventory, and supply chain systems, enterprises can achieve measurable revenue increases and operational efficiency gains.
- However, adopting AI comes with potential risks, such as exposure of sensitive data, AI biases or hallucinations, integration complexities, the need for responsible AI governance, and balancing initial investments with proving measurable business outcomes.
- Vendors like Oracle, SAP, Workday, Microsoft, ServiceNow, and Salesforce are ending discounting and pushing high-margin AI products, transitioning from an era of experimentation to one of monetization, as observed by Forrester.
