Learning to Love AI—and Getting it to Love You Back
Learning to Love AI—and Getting it to Love You Back
Learning to Love AI—and Getting it to Love You Back
Learning to Love AI—and Getting it to Love You Back
The market is overflowing with shiny AI tools. Each one promising to save you hours, make you smarter, and transform your business overnight. We already know AI can work wonders—but knowing it can do this isn’t enough.
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The market is overflowing with shiny AI tools. Each one promising to save you hours, make you smarter, and transform your business overnight. We already know AI can work wonders—but knowing it can do this isn’t enough.
Share
The market is overflowing with shiny AI tools. Each one promising to save you hours, make you smarter, and transform your business overnight. We already know AI can work wonders—but knowing it can do this isn’t enough.
I’ve spent the last few months on an outrageous number of customer calls, working with teams as they try to scope, test, and implement AI into their day-to-day. The ambition and capability is there—but one theme keeps surfacing: most people struggle with how to implement AI. Not with the capabilities, but with the strategy.
It sounds trivial, but it’s not. Get it wrong and your LLM gives you a polite muddle and you lose hope. Get it right and it becomes a trusted colleague you can actually rely on. What follows isn’t a grand thesis on AI, but some tactical reflections from the field: patterns I’ve seen, mistakes worth avoiding, and practices that help teams get started faster and get value sooner.
I’ve spent the last few months on an outrageous number of customer calls, working with teams as they try to scope, test, and implement AI into their day-to-day. The ambition and capability is there—but one theme keeps surfacing: most people struggle with how to implement AI. Not with the capabilities, but with the strategy.
It sounds trivial, but it’s not. Get it wrong and your LLM gives you a polite muddle and you lose hope. Get it right and it becomes a trusted colleague you can actually rely on. What follows isn’t a grand thesis on AI, but some tactical reflections from the field: patterns I’ve seen, mistakes worth avoiding, and practices that help teams get started faster and get value sooner.
I’ve spent the last few months on an outrageous number of customer calls, working with teams as they try to scope, test, and implement AI into their day-to-day. The ambition and capability is there—but one theme keeps surfacing: most people struggle with how to implement AI. Not with the capabilities, but with the strategy.
It sounds trivial, but it’s not. Get it wrong and your LLM gives you a polite muddle and you lose hope. Get it right and it becomes a trusted colleague you can actually rely on. What follows isn’t a grand thesis on AI, but some tactical reflections from the field: patterns I’ve seen, mistakes worth avoiding, and practices that help teams get started faster and get value sooner.
I. Start Small, Win Early, Build Momentum
The market is overflowing with shiny AI tools. Each one promising to save you hours, make you smarter, and transform your business overnight. We already know AI can work wonders—but knowing it can do this isn’t enough.
To get to value, you need more than the right tools. You need the right data, and you need the right strategy. This article will focus on the latter (if you have a great customer platform like Planhat, the former is not an issue). This isn’t a radical claim. As McKinsey & Co. put it in a report last year: “Competitive advantage of GenAI comes from…capabilities to deploy and improve solutions at scale—rewiring the business.” Read the full report here.
What I’ve noticed from working with the early adopters: the key is to start small, with early wins. Then, expand the number of AI use cases before scaling towards end-to-end AI processes. This staged approach makes adoption manageable, keeps your team confident, and ensures that value compounds with every step. Bring AI in, let it grow together with you and your business, then allow it to reshape how your team works.
What follows is a guide on how to start loving your AI, and how to let it love you back, with early wins and fast value-creation that grows into lasting impact.
“What I’ve noticed from working with the early adopters: The key is to start small. Bring AI in, let it grow together with you and your business. Then, allow it to reshape how your team works.”
Julia Sommarlund
Product Manager
Planhat
I. Start Small, Win Early, Build Momentum
The market is overflowing with shiny AI tools. Each one promising to save you hours, make you smarter, and transform your business overnight. We already know AI can work wonders—but knowing it can do this isn’t enough.
To get to value, you need more than the right tools. You need the right data, and you need the right strategy. This article will focus on the latter (if you have a great customer platform like Planhat, the former is not an issue). This isn’t a radical claim. As McKinsey & Co. put it in a report last year: “Competitive advantage of GenAI comes from…capabilities to deploy and improve solutions at scale—rewiring the business.” Read the full report here.
What I’ve noticed from working with the early adopters: the key is to start small, with early wins. Then, expand the number of AI use cases before scaling towards end-to-end AI processes. This staged approach makes adoption manageable, keeps your team confident, and ensures that value compounds with every step. Bring AI in, let it grow together with you and your business, then allow it to reshape how your team works.
What follows is a guide on how to start loving your AI, and how to let it love you back, with early wins and fast value-creation that grows into lasting impact.
“What I’ve noticed from working with the early adopters: The key is to start small. Bring AI in, let it grow together with you and your business. Then, allow it to reshape how your team works.”
Julia Sommarlund
Product Manager
Planhat
I. Start Small, Win Early, Build Momentum
The market is overflowing with shiny AI tools. Each one promising to save you hours, make you smarter, and transform your business overnight. We already know AI can work wonders—but knowing it can do this isn’t enough.
To get to value, you need more than the right tools. You need the right data, and you need the right strategy. This article will focus on the latter (if you have a great customer platform like Planhat, the former is not an issue). This isn’t a radical claim. As McKinsey & Co. put it in a report last year: “Competitive advantage of GenAI comes from…capabilities to deploy and improve solutions at scale—rewiring the business.” Read the full report here.
What I’ve noticed from working with the early adopters: the key is to start small, with early wins. Then, expand the number of AI use cases before scaling towards end-to-end AI processes. This staged approach makes adoption manageable, keeps your team confident, and ensures that value compounds with every step. Bring AI in, let it grow together with you and your business, then allow it to reshape how your team works.
What follows is a guide on how to start loving your AI, and how to let it love you back, with early wins and fast value-creation that grows into lasting impact.
“What I’ve noticed from working with the early adopters: The key is to start small. Bring AI in, let it grow together with you and your business. Then, allow it to reshape how your team works.”
Julia Sommarlund
Product Manager
Planhat
II. Begin with the Wonders You Know
We all have tasks that none of us enjoy.
Writing account summaries, combing through call transcripts, pulling together lists of opportunities hidden in scattered conversations. No hot take: this is where AI thrives. It automates the repetitive, the mundane, the tactical. What once took hours now takes seconds. But its not only about increasing productivity. The real win is emotional—when AI takes on the mundane, your team feels supported.
Work with your AI tool to implement workflows like:
Writing account summaries
Personalizing outreach
Generating opportunities from call transcripts
Meeting preparation
Automating Sales to Customer Success handovers
…Or just use Templated Automations in Planhat for all of the above.
As a result, your team have more hours for strategic work and less frustration from workload.
“But its not only about increasing productivity. The real win is emotional—when AI takes on the mundane, your team feels supported.”
II. Begin with the Wonders You Know
We all have tasks that none of us enjoy.
Writing account summaries, combing through call transcripts, pulling together lists of opportunities hidden in scattered conversations. No hot take: this is where AI thrives. It automates the repetitive, the mundane, the tactical. What once took hours now takes seconds. But its not only about increasing productivity. The real win is emotional—when AI takes on the mundane, your team feels supported.
Work with your AI tool to implement workflows like:
Writing account summaries
Personalizing outreach
Generating opportunities from call transcripts
Meeting preparation
Automating Sales to Customer Success handovers
…Or just use Templated Automations in Planhat for all of the above.
As a result, your team have more hours for strategic work and less frustration from workload.
“But its not only about increasing productivity. The real win is emotional—when AI takes on the mundane, your team feels supported.”
II. Begin with the Wonders You Know
We all have tasks that none of us enjoy.
Writing account summaries, combing through call transcripts, pulling together lists of opportunities hidden in scattered conversations. No hot take: this is where AI thrives. It automates the repetitive, the mundane, the tactical. What once took hours now takes seconds. But its not only about increasing productivity. The real win is emotional—when AI takes on the mundane, your team feels supported.
Work with your AI tool to implement workflows like:
Writing account summaries
Personalizing outreach
Generating opportunities from call transcripts
Meeting preparation
Automating Sales to Customer Success handovers
…Or just use Templated Automations in Planhat for all of the above.
As a result, your team have more hours for strategic work and less frustration from workload.
“But its not only about increasing productivity. The real win is emotional—when AI takes on the mundane, your team feels supported.”
III. Bring in the Context You Don’t Usually Have
The next step is to widen the lens. No more late-night searching for customer news. No more scouring LinkedIn for role changes. No more trying to keep tabs on shifting industry signals and market dynamics.
AI can enrich your customer data with external context, and the effect is profound: conversations feel better prepared, meetings more relevant, and engagements more personalised. Instead of showing up with assumptions, your team shows up with insight and understanding.
High-value use cases across our customer base include:
“Enrich my leads”
“Summarise company news and recent financial reports”
“Notify me of key stakeholder changes”
“Run a risk assessment on the industry“
Again, these are all available as plug-and-play templates in Planhat, so you can get up and running in a matter of minutes.
This will give you richer context in every interaction, smarter preparation and customers will feel better understood—because you actually understand them better.
III. Bring in the Context You Don’t Usually Have
The next step is to widen the lens. No more late-night searching for customer news. No more scouring LinkedIn for role changes. No more trying to keep tabs on shifting industry signals and market dynamics.
AI can enrich your customer data with external context, and the effect is profound: conversations feel better prepared, meetings more relevant, and engagements more personalised. Instead of showing up with assumptions, your team shows up with insight and understanding.
High-value use cases across our customer base include:
“Enrich my leads”
“Summarise company news and recent financial reports”
“Notify me of key stakeholder changes”
“Run a risk assessment on the industry“
Again, these are all available as plug-and-play templates in Planhat, so you can get up and running in a matter of minutes.
This will give you richer context in every interaction, smarter preparation and customers will feel better understood—because you actually understand them better.
III. Bring in the Context You Don’t Usually Have
The next step is to widen the lens. No more late-night searching for customer news. No more scouring LinkedIn for role changes. No more trying to keep tabs on shifting industry signals and market dynamics.
AI can enrich your customer data with external context, and the effect is profound: conversations feel better prepared, meetings more relevant, and engagements more personalised. Instead of showing up with assumptions, your team shows up with insight and understanding.
High-value use cases across our customer base include:
“Enrich my leads”
“Summarise company news and recent financial reports”
“Notify me of key stakeholder changes”
“Run a risk assessment on the industry“
Again, these are all available as plug-and-play templates in Planhat, so you can get up and running in a matter of minutes.
This will give you richer context in every interaction, smarter preparation and customers will feel better understood—because you actually understand them better.
IV. Move from Reactive to Proactive
Once AI is trusted as the admin assistant and external researcher, it’s time to invite it into the heartbeat of your business: customer health. No more lagging indicators: let AI note down sentiment across tickets, emails, and calls, categorise conversations, and pull patterns from usage data and renewal timelines. Feed all of it into a dynamic health score that evolves with reality.
Turn signals into action with AI through flows such as:
“Include prospect sentiment in lead score”
”Notify me about a renewal discussion with a negative sentiment”
“Use customer sentiment to anchor my customer health scores”
And then use those scores to trigger targeted workflows such as: escalate to a manager, draft a customer email, suggest a playbook.
Yet again, sentiment and conversation classification comes out-of-the-box in Planhat.
As a consequence, your team detects risks earlier, intervenes faster, and protects revenue with proactive engagement. Customers feel supported, not surprised.
IV. Move from Reactive to Proactive
Once AI is trusted as the admin assistant and external researcher, it’s time to invite it into the heartbeat of your business: customer health. No more lagging indicators: let AI note down sentiment across tickets, emails, and calls, categorise conversations, and pull patterns from usage data and renewal timelines. Feed all of it into a dynamic health score that evolves with reality.
Turn signals into action with AI through flows such as:
“Include prospect sentiment in lead score”
”Notify me about a renewal discussion with a negative sentiment”
“Use customer sentiment to anchor my customer health scores”
And then use those scores to trigger targeted workflows such as: escalate to a manager, draft a customer email, suggest a playbook.
Yet again, sentiment and conversation classification comes out-of-the-box in Planhat.
As a consequence, your team detects risks earlier, intervenes faster, and protects revenue with proactive engagement. Customers feel supported, not surprised.
IV. Move from Reactive to Proactive
Once AI is trusted as the admin assistant and external researcher, it’s time to invite it into the heartbeat of your business: customer health. No more lagging indicators: let AI note down sentiment across tickets, emails, and calls, categorise conversations, and pull patterns from usage data and renewal timelines. Feed all of it into a dynamic health score that evolves with reality.
Turn signals into action with AI through flows such as:
“Include prospect sentiment in lead score”
”Notify me about a renewal discussion with a negative sentiment”
“Use customer sentiment to anchor my customer health scores”
And then use those scores to trigger targeted workflows such as: escalate to a manager, draft a customer email, suggest a playbook.
Yet again, sentiment and conversation classification comes out-of-the-box in Planhat.
As a consequence, your team detects risks earlier, intervenes faster, and protects revenue with proactive engagement. Customers feel supported, not surprised.
V. Let it See the Bigger Picture
The next frontier is insight at scale. By analysing patterns across portfolios, AI helps you answer questions no single customer rep could, such as: What do our churned customers have in common? Where are the early signals of risk? What customer pain points are emerging across feedback?
Leverage data across your customer portfolio to:
Aggregate feedback from customers and prospects to identify pain points and feedback to product strategy
Analyse churned customers to understand risk drivers
Identify your ICP based on healthy and well-performing customers across regions and industries
This gives you a strategic edge: decisions based on data, not gut-feel. AI becomes a decisive partner, helping you prioritise, prepare, and shape the direction of your business.
V. Let it See the Bigger Picture
The next frontier is insight at scale. By analysing patterns across portfolios, AI helps you answer questions no single customer rep could, such as: What do our churned customers have in common? Where are the early signals of risk? What customer pain points are emerging across feedback?
Leverage data across your customer portfolio to:
Aggregate feedback from customers and prospects to identify pain points and feedback to product strategy
Analyse churned customers to understand risk drivers
Identify your ICP based on healthy and well-performing customers across regions and industries
This gives you a strategic edge: decisions based on data, not gut-feel. AI becomes a decisive partner, helping you prioritise, prepare, and shape the direction of your business.
V. Let it See the Bigger Picture
The next frontier is insight at scale. By analysing patterns across portfolios, AI helps you answer questions no single customer rep could, such as: What do our churned customers have in common? Where are the early signals of risk? What customer pain points are emerging across feedback?
Leverage data across your customer portfolio to:
Aggregate feedback from customers and prospects to identify pain points and feedback to product strategy
Analyse churned customers to understand risk drivers
Identify your ICP based on healthy and well-performing customers across regions and industries
This gives you a strategic edge: decisions based on data, not gut-feel. AI becomes a decisive partner, helping you prioritise, prepare, and shape the direction of your business.
The Punchline: Strategy Creates Compounding Value
Yes, the tools are brilliant. The demos are dazzling. But real value doesn’t come from exciting features, it comes from anchoring AI in data and a sustainable strategy.
Companies that win with AI are the ones with early wins that build momentum through practical use cases which solve real problems—most commonly by:
Automating the manual work
Enriching customer data
Monitoring and take action on customer health
Analyzing cross-portfolio to uncover trends and insights
These are things early adopters have already implemented.
Follow their lead and AI becomes woven into the way you work—creating efficiency, protecting revenue, and uncovering insights you’d otherwise miss.
Small wins, big shifts—that’s the compounding power of AI.
The Punchline: Strategy Creates Compounding Value
Yes, the tools are brilliant. The demos are dazzling. But real value doesn’t come from exciting features, it comes from anchoring AI in data and a sustainable strategy.
Companies that win with AI are the ones with early wins that build momentum through practical use cases which solve real problems—most commonly by:
Automating the manual work
Enriching customer data
Monitoring and take action on customer health
Analyzing cross-portfolio to uncover trends and insights
These are things early adopters have already implemented.
Follow their lead and AI becomes woven into the way you work—creating efficiency, protecting revenue, and uncovering insights you’d otherwise miss.
Small wins, big shifts—that’s the compounding power of AI.
The Punchline: Strategy Creates Compounding Value
Yes, the tools are brilliant. The demos are dazzling. But real value doesn’t come from exciting features, it comes from anchoring AI in data and a sustainable strategy.
Companies that win with AI are the ones with early wins that build momentum through practical use cases which solve real problems—most commonly by:
Automating the manual work
Enriching customer data
Monitoring and take action on customer health
Analyzing cross-portfolio to uncover trends and insights
These are things early adopters have already implemented.
Follow their lead and AI becomes woven into the way you work—creating efficiency, protecting revenue, and uncovering insights you’d otherwise miss.
Small wins, big shifts—that’s the compounding power of AI.
Planhat AI Platform
Planhat AI Platform
Planhat AI Platform
Customers
© 2025 Planhat AB
Customers
© 2025 Planhat AB
Customers
© 2025 Planhat AB
Customers
© 2025 Planhat AB