AI-driven customer experience strategy 2026
AI-driven customer experience strategy 2026
B2B buyers want proof, vendors reshape CX with AI, cloud outages expose risks, and commerce personalization scales — what leaders must do.
B2B buyers want proof, vendors reshape CX with AI, cloud outages expose risks, and commerce personalization scales — what leaders must do.
Oct 31, 2025
Oct 31, 2025
Oct 31, 2025
AI-driven customer experience strategy: proof, resilience, and personalization
The business world is moving toward an AI-driven customer experience strategy that demands proof, not promises. Therefore, leaders must show measurable results and clear governance to win deals. However, market shifts and outages are also exposing operational risks. Additionally, new consumer tools show how AI personalizes commerce. This blog pulls together five recent industry moves to explain what executives should watch, what to change, and how to prepare.
## Forrester: Proof not promises — why B2B buyers have changed
Forrester’s research signals a major shift: B2B buyers in 2026 will prioritize proof of outcomes over vendor promises. Therefore, sales and marketing teams that rely on persuasive messaging will need new playbooks. For example, vendors should move from abstract claims to case studies that show measurable ROI and to pre-sales processes that demonstrate real outcomes. Additionally, procurement teams are tightening budgets because of economic uncertainty. As a result, the buyer’s default question has shifted from “Can you do it?” to “Can you prove it works for us?”
This change affects the whole commercial cycle. Sales must coordinate with delivery and customer success to produce evidence early. Moreover, product teams will need telemetry that ties features to business metrics. Consequently, legal and compliance groups should prepare outcome-based contracts and clear SLAs. In short, companies that can quantify value and present reproducible proofs will win more RFPs and shorten procurement cycles. Looking ahead, vendors that invest in measurement frameworks and transparent reporting will gain trust and competitive advantage.
Source: Digital Commerce 360
ServiceNow and the AI-driven customer experience strategy for workflows
ServiceNow used its strong quarterly results to expand an AI-driven customer experience strategy across enterprise workflows. For example, the company reported $3.407 billion in revenue — a 22% year-over-year increase — and then doubled down on AI as the next frontier. Therefore, customers can expect more automation, smarter routing, and integrated CRM capabilities that reduce friction across service teams.
However, this is more than a product update. It signals how major enterprise platforms are positioning AI as a workflow fabric. Additionally, ServiceNow’s approach shows vendors will bundle AI into core processes rather than offer it as a bolt-on. As a result, organizations that run complex service operations should evaluate how embedded AI can reduce manual steps and improve response times. Moreover, IT and business leaders must clarify ownership of these automations. For instance, governance structures will be needed to ensure AI suggestions are explainable and aligned with corporate policy.
Looking forward, the competitive landscape will reward platforms that make AI operational and safe. Consequently, enterprises should pilot integrated AI workflows while building measurement to show outcomes. Therefore, pairing automation with proof points will be essential for internal buy-in and vendor selection.
Source: CX Today
How Microsoft’s moves fit an AI-driven customer experience strategy
Microsoft’s recent earnings discussion highlighted how its AI strategy is reshaping customer experience across products. Therefore, enterprises are watching how a major vendor applies generative models to CRM, analytics, and support systems. For example, insights buried in the call described efforts to make customer interactions more predictive and contextual, which can reduce effort for both agents and customers.
Moreover, Microsoft’s scale matters. Its approach demonstrates how AI can be integrated into the platforms that many companies already use. As a result, buyers should assess not only features but also vendor roadmaps and ecosystem integration. Additionally, this moment calls for attention to data governance: companies must ensure that the data feeding AI is accurate, consented, and auditable. Consequently, the organizations that combine Microsoft’s platform capabilities with rigorous governance and measurement will likely get the greatest business value.
Finally, leaders should treat vendor AI strategies as strategic signals. For instance, a vendor prioritizing explainability and enterprise controls offers a different long-term risk profile than one focused only on novelty. Therefore, aligning vendor choice with internal risk tolerance and measurement needs will be critical.
Source: CX Today
Cloud outages and why resilience matters for CX platforms
Recent cloud disruptions have exposed how fragile customer experience platforms can be when core cloud services fail. For example, Microsoft Azure experienced a service disruption shortly after a major AWS outage, and that incident affected customer applications including the communications protocol that runs Dynamics 365 Contact Center. Therefore, even top-tier clouds can become single points of failure for business-critical CX systems.
Consequently, enterprises must rethink resilience and contingency plans. Moreover, dependency mapping is essential: IT teams should know which customer journeys rely on which cloud services. As a result, organizations should build multi-cloud strategies, graceful degradation, and failover plans that preserve the most important customer interactions. Additionally, service providers should be transparent about dependencies and recovery SLAs so buyers can assess operational risk.
Finally, governance matters more than ever. For example, contracts and runbooks should specify incident roles, customer notification plans, and compensation. Therefore, marrying operational resilience with proof-of-outcome reporting will protect revenue and reputation when things go wrong. In short, resilience planning is a board-level concern for any company that markets itself on great customer experiences.
Source: CX Today
Behr’s Chathue shows consumer AI personalization at work
Behr Paint’s partnership with Google Cloud produced Chathue, an AI color assistant that personalizes paint selection for homeowners. Therefore, this is a clear example of AI moving from novelty to everyday commerce use. For instance, shoppers can now get tailored recommendations without the guesswork, which reduces friction and increases conversion potential.
Moreover, the use case highlights how AI can enhance physical retail experiences. As a result, brands in consumer sectors should explore similar assistants for category choices, styling, and configuration. Additionally, integrating these tools with cloud platforms makes it easier to scale personalization across channels. However, companies must keep user experience simple and ensure recommendations are accurate to avoid eroding trust.
Finally, for enterprise sellers and commerce teams, this signals a new expectation: customers will increasingly expect conversational, helpful, and context-aware shopping aids. Therefore, building or partnering for those capabilities should be part of a broader AI-driven customer experience strategy that emphasizes measurable impact on conversion and satisfaction.
Source: Digital Commerce 360
Final Reflection: Connecting proof, platforms, and resilience
Taken together, these five stories form a clear narrative for 2026. First, buyers now demand proof of outcomes, not polished promises. Therefore, vendors and internal teams must build measurement and transparency into every offering. Second, major platform vendors like ServiceNow and Microsoft are embedding AI across workflows and CX tools, which creates opportunity but also responsibility. Consequently, governance, explainability, and outcome-linked SLAs will separate winners from laggards. Third, cloud outages remind us that operational resilience must accompany innovation. In short, the future of customer experience is AI-driven, but it must be verifiable and resilient. For leaders, the path is straightforward: prioritize measurable pilots, align governance with vendor choice, and bake resilience into customer journeys. Doing so will turn AI investments into repeatable business value.
AI-driven customer experience strategy: proof, resilience, and personalization
The business world is moving toward an AI-driven customer experience strategy that demands proof, not promises. Therefore, leaders must show measurable results and clear governance to win deals. However, market shifts and outages are also exposing operational risks. Additionally, new consumer tools show how AI personalizes commerce. This blog pulls together five recent industry moves to explain what executives should watch, what to change, and how to prepare.
## Forrester: Proof not promises — why B2B buyers have changed
Forrester’s research signals a major shift: B2B buyers in 2026 will prioritize proof of outcomes over vendor promises. Therefore, sales and marketing teams that rely on persuasive messaging will need new playbooks. For example, vendors should move from abstract claims to case studies that show measurable ROI and to pre-sales processes that demonstrate real outcomes. Additionally, procurement teams are tightening budgets because of economic uncertainty. As a result, the buyer’s default question has shifted from “Can you do it?” to “Can you prove it works for us?”
This change affects the whole commercial cycle. Sales must coordinate with delivery and customer success to produce evidence early. Moreover, product teams will need telemetry that ties features to business metrics. Consequently, legal and compliance groups should prepare outcome-based contracts and clear SLAs. In short, companies that can quantify value and present reproducible proofs will win more RFPs and shorten procurement cycles. Looking ahead, vendors that invest in measurement frameworks and transparent reporting will gain trust and competitive advantage.
Source: Digital Commerce 360
ServiceNow and the AI-driven customer experience strategy for workflows
ServiceNow used its strong quarterly results to expand an AI-driven customer experience strategy across enterprise workflows. For example, the company reported $3.407 billion in revenue — a 22% year-over-year increase — and then doubled down on AI as the next frontier. Therefore, customers can expect more automation, smarter routing, and integrated CRM capabilities that reduce friction across service teams.
However, this is more than a product update. It signals how major enterprise platforms are positioning AI as a workflow fabric. Additionally, ServiceNow’s approach shows vendors will bundle AI into core processes rather than offer it as a bolt-on. As a result, organizations that run complex service operations should evaluate how embedded AI can reduce manual steps and improve response times. Moreover, IT and business leaders must clarify ownership of these automations. For instance, governance structures will be needed to ensure AI suggestions are explainable and aligned with corporate policy.
Looking forward, the competitive landscape will reward platforms that make AI operational and safe. Consequently, enterprises should pilot integrated AI workflows while building measurement to show outcomes. Therefore, pairing automation with proof points will be essential for internal buy-in and vendor selection.
Source: CX Today
How Microsoft’s moves fit an AI-driven customer experience strategy
Microsoft’s recent earnings discussion highlighted how its AI strategy is reshaping customer experience across products. Therefore, enterprises are watching how a major vendor applies generative models to CRM, analytics, and support systems. For example, insights buried in the call described efforts to make customer interactions more predictive and contextual, which can reduce effort for both agents and customers.
Moreover, Microsoft’s scale matters. Its approach demonstrates how AI can be integrated into the platforms that many companies already use. As a result, buyers should assess not only features but also vendor roadmaps and ecosystem integration. Additionally, this moment calls for attention to data governance: companies must ensure that the data feeding AI is accurate, consented, and auditable. Consequently, the organizations that combine Microsoft’s platform capabilities with rigorous governance and measurement will likely get the greatest business value.
Finally, leaders should treat vendor AI strategies as strategic signals. For instance, a vendor prioritizing explainability and enterprise controls offers a different long-term risk profile than one focused only on novelty. Therefore, aligning vendor choice with internal risk tolerance and measurement needs will be critical.
Source: CX Today
Cloud outages and why resilience matters for CX platforms
Recent cloud disruptions have exposed how fragile customer experience platforms can be when core cloud services fail. For example, Microsoft Azure experienced a service disruption shortly after a major AWS outage, and that incident affected customer applications including the communications protocol that runs Dynamics 365 Contact Center. Therefore, even top-tier clouds can become single points of failure for business-critical CX systems.
Consequently, enterprises must rethink resilience and contingency plans. Moreover, dependency mapping is essential: IT teams should know which customer journeys rely on which cloud services. As a result, organizations should build multi-cloud strategies, graceful degradation, and failover plans that preserve the most important customer interactions. Additionally, service providers should be transparent about dependencies and recovery SLAs so buyers can assess operational risk.
Finally, governance matters more than ever. For example, contracts and runbooks should specify incident roles, customer notification plans, and compensation. Therefore, marrying operational resilience with proof-of-outcome reporting will protect revenue and reputation when things go wrong. In short, resilience planning is a board-level concern for any company that markets itself on great customer experiences.
Source: CX Today
Behr’s Chathue shows consumer AI personalization at work
Behr Paint’s partnership with Google Cloud produced Chathue, an AI color assistant that personalizes paint selection for homeowners. Therefore, this is a clear example of AI moving from novelty to everyday commerce use. For instance, shoppers can now get tailored recommendations without the guesswork, which reduces friction and increases conversion potential.
Moreover, the use case highlights how AI can enhance physical retail experiences. As a result, brands in consumer sectors should explore similar assistants for category choices, styling, and configuration. Additionally, integrating these tools with cloud platforms makes it easier to scale personalization across channels. However, companies must keep user experience simple and ensure recommendations are accurate to avoid eroding trust.
Finally, for enterprise sellers and commerce teams, this signals a new expectation: customers will increasingly expect conversational, helpful, and context-aware shopping aids. Therefore, building or partnering for those capabilities should be part of a broader AI-driven customer experience strategy that emphasizes measurable impact on conversion and satisfaction.
Source: Digital Commerce 360
Final Reflection: Connecting proof, platforms, and resilience
Taken together, these five stories form a clear narrative for 2026. First, buyers now demand proof of outcomes, not polished promises. Therefore, vendors and internal teams must build measurement and transparency into every offering. Second, major platform vendors like ServiceNow and Microsoft are embedding AI across workflows and CX tools, which creates opportunity but also responsibility. Consequently, governance, explainability, and outcome-linked SLAs will separate winners from laggards. Third, cloud outages remind us that operational resilience must accompany innovation. In short, the future of customer experience is AI-driven, but it must be verifiable and resilient. For leaders, the path is straightforward: prioritize measurable pilots, align governance with vendor choice, and bake resilience into customer journeys. Doing so will turn AI investments into repeatable business value.
AI-driven customer experience strategy: proof, resilience, and personalization
The business world is moving toward an AI-driven customer experience strategy that demands proof, not promises. Therefore, leaders must show measurable results and clear governance to win deals. However, market shifts and outages are also exposing operational risks. Additionally, new consumer tools show how AI personalizes commerce. This blog pulls together five recent industry moves to explain what executives should watch, what to change, and how to prepare.
## Forrester: Proof not promises — why B2B buyers have changed
Forrester’s research signals a major shift: B2B buyers in 2026 will prioritize proof of outcomes over vendor promises. Therefore, sales and marketing teams that rely on persuasive messaging will need new playbooks. For example, vendors should move from abstract claims to case studies that show measurable ROI and to pre-sales processes that demonstrate real outcomes. Additionally, procurement teams are tightening budgets because of economic uncertainty. As a result, the buyer’s default question has shifted from “Can you do it?” to “Can you prove it works for us?”
This change affects the whole commercial cycle. Sales must coordinate with delivery and customer success to produce evidence early. Moreover, product teams will need telemetry that ties features to business metrics. Consequently, legal and compliance groups should prepare outcome-based contracts and clear SLAs. In short, companies that can quantify value and present reproducible proofs will win more RFPs and shorten procurement cycles. Looking ahead, vendors that invest in measurement frameworks and transparent reporting will gain trust and competitive advantage.
Source: Digital Commerce 360
ServiceNow and the AI-driven customer experience strategy for workflows
ServiceNow used its strong quarterly results to expand an AI-driven customer experience strategy across enterprise workflows. For example, the company reported $3.407 billion in revenue — a 22% year-over-year increase — and then doubled down on AI as the next frontier. Therefore, customers can expect more automation, smarter routing, and integrated CRM capabilities that reduce friction across service teams.
However, this is more than a product update. It signals how major enterprise platforms are positioning AI as a workflow fabric. Additionally, ServiceNow’s approach shows vendors will bundle AI into core processes rather than offer it as a bolt-on. As a result, organizations that run complex service operations should evaluate how embedded AI can reduce manual steps and improve response times. Moreover, IT and business leaders must clarify ownership of these automations. For instance, governance structures will be needed to ensure AI suggestions are explainable and aligned with corporate policy.
Looking forward, the competitive landscape will reward platforms that make AI operational and safe. Consequently, enterprises should pilot integrated AI workflows while building measurement to show outcomes. Therefore, pairing automation with proof points will be essential for internal buy-in and vendor selection.
Source: CX Today
How Microsoft’s moves fit an AI-driven customer experience strategy
Microsoft’s recent earnings discussion highlighted how its AI strategy is reshaping customer experience across products. Therefore, enterprises are watching how a major vendor applies generative models to CRM, analytics, and support systems. For example, insights buried in the call described efforts to make customer interactions more predictive and contextual, which can reduce effort for both agents and customers.
Moreover, Microsoft’s scale matters. Its approach demonstrates how AI can be integrated into the platforms that many companies already use. As a result, buyers should assess not only features but also vendor roadmaps and ecosystem integration. Additionally, this moment calls for attention to data governance: companies must ensure that the data feeding AI is accurate, consented, and auditable. Consequently, the organizations that combine Microsoft’s platform capabilities with rigorous governance and measurement will likely get the greatest business value.
Finally, leaders should treat vendor AI strategies as strategic signals. For instance, a vendor prioritizing explainability and enterprise controls offers a different long-term risk profile than one focused only on novelty. Therefore, aligning vendor choice with internal risk tolerance and measurement needs will be critical.
Source: CX Today
Cloud outages and why resilience matters for CX platforms
Recent cloud disruptions have exposed how fragile customer experience platforms can be when core cloud services fail. For example, Microsoft Azure experienced a service disruption shortly after a major AWS outage, and that incident affected customer applications including the communications protocol that runs Dynamics 365 Contact Center. Therefore, even top-tier clouds can become single points of failure for business-critical CX systems.
Consequently, enterprises must rethink resilience and contingency plans. Moreover, dependency mapping is essential: IT teams should know which customer journeys rely on which cloud services. As a result, organizations should build multi-cloud strategies, graceful degradation, and failover plans that preserve the most important customer interactions. Additionally, service providers should be transparent about dependencies and recovery SLAs so buyers can assess operational risk.
Finally, governance matters more than ever. For example, contracts and runbooks should specify incident roles, customer notification plans, and compensation. Therefore, marrying operational resilience with proof-of-outcome reporting will protect revenue and reputation when things go wrong. In short, resilience planning is a board-level concern for any company that markets itself on great customer experiences.
Source: CX Today
Behr’s Chathue shows consumer AI personalization at work
Behr Paint’s partnership with Google Cloud produced Chathue, an AI color assistant that personalizes paint selection for homeowners. Therefore, this is a clear example of AI moving from novelty to everyday commerce use. For instance, shoppers can now get tailored recommendations without the guesswork, which reduces friction and increases conversion potential.
Moreover, the use case highlights how AI can enhance physical retail experiences. As a result, brands in consumer sectors should explore similar assistants for category choices, styling, and configuration. Additionally, integrating these tools with cloud platforms makes it easier to scale personalization across channels. However, companies must keep user experience simple and ensure recommendations are accurate to avoid eroding trust.
Finally, for enterprise sellers and commerce teams, this signals a new expectation: customers will increasingly expect conversational, helpful, and context-aware shopping aids. Therefore, building or partnering for those capabilities should be part of a broader AI-driven customer experience strategy that emphasizes measurable impact on conversion and satisfaction.
Source: Digital Commerce 360
Final Reflection: Connecting proof, platforms, and resilience
Taken together, these five stories form a clear narrative for 2026. First, buyers now demand proof of outcomes, not polished promises. Therefore, vendors and internal teams must build measurement and transparency into every offering. Second, major platform vendors like ServiceNow and Microsoft are embedding AI across workflows and CX tools, which creates opportunity but also responsibility. Consequently, governance, explainability, and outcome-linked SLAs will separate winners from laggards. Third, cloud outages remind us that operational resilience must accompany innovation. In short, the future of customer experience is AI-driven, but it must be verifiable and resilient. For leaders, the path is straightforward: prioritize measurable pilots, align governance with vendor choice, and bake resilience into customer journeys. Doing so will turn AI investments into repeatable business value.
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Let's get your business to the next level
Email Address:
sales@swlconsulting.com
Address:
Av. del Libertador, 1000
Follow Us:
CONTACT US
Let's get your business to the next level
Email Address:
sales@swlconsulting.com
Address:
Av. del Libertador, 1000
Follow Us:
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