Hannah Simons
Sales reps are drowning in tasks that have nothing to do with selling. 82% say building relationships is the most enjoyable part of their role, but most spend their time buried in admin and CRM upkeep instead.
It’s no surprise that 81% of sales professionals are already experimenting with AI in a bid to boost productivity and reduce turnover of their bored and burned out team members. But without a clear plan, it’s easy to invest in the tech without ever seeing a return.
This article breaks down eight practical ways to embed AI into your sales workflows so your team can spend more time selling and less time stuck in spreadsheets. We'll also discuss how to sidestep some common challenges associated with mistaking AI for a magic bullet.
Sales can be a great industry to grow your professional capabilities and build on transferable skills learned in education. Salespeople can develop their careers based on their individual interests and ideal lifestyle, making sales an exciting career choice for graduates entering the job market.
How smart sales teams embed AI into everyday workflows
To get real results from AI, smart sales teams shouldn’t treat it as a shiny add-on. From hiring to forecasting, the real power of AI shows up when it’s mapped to core sales workflows with clear objectives and outcomes. Here are eight high-impact ways sales teams use AI to create more time for work that moves the needle.
1. Removing bias from the sales hiring process
We often think of AI as a tool that can help sales professionals once they’re firmly embedded in the organisation and already executing their workflows. But AI is also integral to hiring the most talented sales people in the first place — not just the people who seem like a “good fit.”
Most sales hiring strategies still lean too heavily on instinct when searching for their company’s next generation of sales talent. A confident interview, a polished CV, and a few shared interests with the hiring panel can lead to a candidate who “feels right” but underdelivers once they’re in the seat.
Why? Because instinct often reinforces bias and narrows the talent pool, unintentionally filtering out high-potential candidates from underrepresented backgrounds.
As an alternative, AI creates a more objective, consistent hiring process by:
- Standardising skills assessments across candidates so you're comparing like for like
- Assessing behavioural traits, such as coachability or curiosity, with greater accuracy
- Removing irrelevant screening data like educational background or CV polish
- Predicting ramp time and long-term fit using patterns from previous top sales performers
2. Onboarding sales professional faster
Sales leaders often underestimate the time it takes for a new hire to settle in and start performing effectively. In reality, it can take a sales rep five to six months to fully ramp up, which may be even longer in more complex sales cycles.
That’s half a year of coaching and shadowing before you start seeing results from your new sales talent.
AI can’t fast-forward through the learning curve, but it can make the journey a lot more efficient. Smart teams use AI to:
- Deliver more focused onboarding, such as adapting content to each rep’s pace and knowledge gaps
- Spot early blockers by analysing conversations, workflows, and CRM activity
- Support self-led learning with AI-generated practice scenarios rather than static playbooks
3. Driving SDR accountability
Accountability in SDR teams often gets lost in the noise. Targets are clear but the expectations on how to get there aren’t. And when that happens, it’s hard for reps to course-correct or for managers to coach in the right direction.
That’s where AI can sharpen the picture. Rather than sifting through dashboards or chasing status updates, managers can use AI to:
- Keep tabs on key behaviours like outreach consistency, objection handling, or follow-up timing
- Highlight coaching moments based on real patterns, not gut feel
- Keep performance conversations focused on facts, not opinions
4. Syncing customer data across platforms
Most sales teams still work with messy, outdated data. Leads get handed off between tools, notes go missing, and no one’s quite sure which version of the truth to act upon. As a result, only 35% of sales professionals trust the accuracy of their organisation’s data. And it’s a disconnect that creates risk as reps chase down the wrong opportunities and miss those that would have closed.
AI can help people in sales roles clean up the mess by:
- Syncing interaction data across platforms automatically
- Filling in missing details from emails, calls, and CRM entries
- Keeping records up to date without manual effort
The result is a cleaner pipeline, smoother handoffs, and fewer mistakes caused by outdated information. Overall, better data leads to superior decisions and less time lost to chasing the full story.
5. Automating sales admin
Sales reps are hired to sell, but that’s not how they spend their time.
According to Salesforce data, reps only spend 30% of their week actively selling. The rest is swallowed by tasks like updating the CRM, preparing quotes, and chasing internal approvals. Smart teams use AI to swing the balance by:
- Auto-completing CRM entries based on emails, calls, and meetings
- Generating first-draft quotes and proposals
- Scheduling follow-ups and managing pipeline reminders behind the scenes
81% of sales professionals say AI helps them spend less time on manual tasks, and some are already saving up to two hours a day. That time is reinvested where it matters: building pipelines, running better calls, and closing more deals, aka the work sales pros love and are best at.
6. Providing round-the-clock engagement
Leads don’t wait for your team to be available. They get in touch whenever it best suits them, which might be late at night, over the weekend, or during a packed sales meeting.
AI offers a simple way to stay responsive, even when your team is offline. Using chatbots and knowledge bases, AI sales agents can answer basic questions, capture lead details, and guide prospects to useful resources in real time. The bots aren’t supposed to replace your salespeople, but they can hold the conversation until your humans are available to take over.
As buying behaviours shift, this kind of responsiveness is a critical part of the customer journey. HubSpot reports that 52% of sales professionals have seen an increase in B2B buyers using self-serve tools. These buyers are used to finding answers quickly and moving at their own pace. And momentum fades fast when they don’t.
Adding a layer of automation at the top of the funnel prevents good leads from going cold. It also keeps prospects engaged and ensures your team has what they need to follow up quickly, without having to start from scratch.
7. Achieving personalisation at scale
Relevance is what opens doors in modern sales. Buyers are bombarded with outreach, and they can instantly tell when a message wasn’t personalised or written with them in mind.
According to Salesforce, 59% of business buyers say sales reps don’t understand their unique goals — and this miscommunication often leads to stalled deals. On the flip side, 86% of buyers say they’re more likely to make a purchase when they feel understood.
The sales reps who aren’t tailoring their comms aren’t lazy. The reality is that personalisation takes time, and reps don't have enough of it. But AI can lighten the load by:
- Drafting tailored outreach using firmographics, buyer behaviour, and deal history
- Recommending content or messaging based on customer needs and journey stage
- Providing timely context so reps don’t start cold, even with brand new accounts
The result is outreach that feels considered rather than canned and a buying experience that builds trust from the start.
8. Predicting pipeline accurately and forecasting sales
Forecasting is one of the hardest parts of a sales leader's job and one of the most exposed. The further up the chain a number goes, the more trust it needs to carry. But when forecasts are built on incomplete or inconsistent data, even the best-case scenarios fall apart under pressure.
Case in point: 67% of sales reps don’t expect to meet their quota this year, and 84% missed it last year. While a lot goes into these numbers, poor pipeline visibility and missed early warning signs are at the heart of the problem.
AI gets ahead of those sales misses and supports forecasting by:
- Identifying which products or services convert best with specific customer profiles
- Flagging stalled deals based on engagement drop-off
- Scoring leads more accurately using a blend of intent signals and historical performance
With clearer signals and fewer surprises, leaders can commit to numbers with confidence and course-correct earlier when things go off track.
3 common challenges to adopting AI in your sales workflows
AI isn’t a switch you can flick to fix your broken sales processes. Like any system, it only works when built on solid foundations. Sales teams that rush implementation or treat AI like a shortcut often see underwhelming results. Here are three common reasons why.
Working with incomplete data sets
AI is only as strong as the data behind it. If your CRM is full of gaps, duplicates, or outdated records, you're not setting the system up to succeed. In fact, 31% of sales teams cite bad or incomplete data as one of the biggest blockers to AI adoption.
Before layering on new technology, it’s worth taking a hard look at the quality of the information you’re feeding into it. If you put rubbish in, you’ll get rubbish out — and in sales, that can mean poor recommendations and bad calls.
Using AI as a crutch
AI works best when you have clearly defined sales processes, including those for qualification and handoff. When teams skip over strategy and try to automate an already-messy process, they just move faster in the wrong direction. As Sales and GTM Strategist and Coach James Casey says,
“AI can't fix a broken sales process. You need clarity on your Ideal Customer Profile (ICP), messaging, and buyer journey first. Only then can AI enhance your sales efforts effectively. Don't let AI be a crutch for a lack of process. Build the system first...then let AI amplify your success.”
Scrimping on AI training
You can’t get value from AI if your team doesn’t know how to use it. Sadly though, 33% of sales teams say insufficient training is one of their top implementation challenges.
Rolling out AI without upskilling your reps is like handing them a Formula 1 car with no driving lessons. With practical training, reps and their managers will learn how AI fits into their daily workflow, where it helps, and where it doesn’t.
Lean on AI to achieve sales success
AI is already reshaping how sales teams work, but without the right systems, structure, and training, it won’t deliver the impact you’re hoping for. Tools alone don’t solve performance gaps; the best results are achieved when your people are equipped to use AI with purpose.
Furza’s AI training programmes are built exactly for that. We work with both frontline sales teams and managers to turn AI from a novelty into part of the day-to-day workflow.
- For sales professionals, our one-day, instructor-led course teaches reps how to cut prep time, boost outreach results, and build better conversations using practical, repeatable prompts — with no prior AI experience required.
- For sales managers, we deliver a hands-on, strategic session that shows leaders how to scale best practices, lead AI-enhanced 1-to-1s, operationalise coaching, and even hire more effectively with the help of structured AI frameworks.
Each course is built around real sales scenarios and mapped to your team’s workflows, not just theory or tool demos.
If you want to embed AI into how your team actually sells, not just experiment with it around the edges, we can help. Ready to turn AI into a strategic advantage for your sales team? Contact Furza today.
