The State of B2B Sales in 2026

I’ve worked in B2B sales now for more than 25 years, and I’ve seen plenty of trends come and go.

Some have genuinely changed the way we sell. Others have created a lot of noise, cost companies a fortune and eventually disappeared.

Looking back at 2026, I think we’re experiencing a bit of both.

Artificial intelligence (AI) has dominated the conversation, particularly in the SaaS industry.

Every week, another company seems to be announcing how it has automated its prospecting, generated thousands of personalised emails or built an outbound sales engine that practically runs itself.

Meanwhile, the sales leaders I’ve spoken with over the past 12 to 18 months have been telling me a rather different story.

Cold outbound conversions are getting worse, meetings aren’t producing enough qualified opportunities, and too many deals are slipping.

There’s a growing disconnect between what we’re being told is possible and what’s actually happening inside sales organisations.

I’m not against AI. Far from it. I use it myself, and I think it offers some tremendous opportunities for salespeople and sales leaders.

However, I also believe we’re in a period where technology is developing much faster than people’s ability to use it properly.

And that creates problems.

In this article, I share my observations on the state of B2B sales in 2026, what I believe is changing in buyer behaviour, and where I think we’re heading in 2027.

Jump to a section:

• AI Has Turned Personalised Outbound Into a Numbers Game
• More Meetings Don’t Mean More Opportunities
• Why B2B Buyers Still Need Salespeople
• Being Known Before Buyers Are Ready Matters More Than Ever
• The Best Use of AI in Sales
• My Predictions for B2B Sales in 2027
• What Sales Leaders Need to Do Differently in 2027
• Final Thoughts
• Frequently Asked Questions

AI Has Turned Personalised Outbound Into a Numbers Game

For the past five to ten years, personalisation has been one of the biggest topics in B2B sales prospecting.

Salespeople have been encouraged to move away from generic email templates and towards highly personalised messaging, using information about the buyer, their company, their industry or something happening within their organisation.

And for good reason.

When somebody takes the time to research your company and write a message that’s genuinely relevant to your situation, it stands a better chance of catching your attention than something sent to another thousand people.

However, AI has changed the economics of personalisation.

Today, a salesperson can feed an AI tool a company website, a contact’s job title and a few basic details, then ask it to write what appears to be a highly personalised email.

They can repeat that process thousands of times without ever visiting a website or properly researching the companies they’re contacting.

In other words, AI has made it possible to personalise outbound emails almost blindfolded.

And that’s where I think the problems begin.

Spend a little time on LinkedIn, and you’ll come across countless GTM companies promoting their latest outbound campaigns. Some are talking about sending hundreds of thousands of AI-personalised emails, often highlighting the number of meetings they’ve generated.

Naturally, salespeople and sales leaders see these claims and start wondering whether they’re falling behind.

If everybody else is apparently getting incredible results from AI-powered prospecting, surely they need to start doing the same?

So they invest in the technology, build automated sequences and increase their outbound volume.

The problem is that much of this activity isn’t genuinely personalised. It’s generic messaging dressed up to look personal.

And buyers are becoming increasingly good at recognising it.

I believe AI has started to undermine the very thing personalisation was supposed to achieve.

Before AI, a well-researched, personalised email could stand out because somebody had clearly made an effort.

Today, even when a salesperson has genuinely researched a buyer and carefully written their message, there’s a reasonable chance the recipient will assume it was generated automatically.

The message might still be relevant, but the trust attached to that personalisation has been weakened.

That’s a significant problem for salespeople who have been doing things properly all along.

It’s also creating more resistance to cold outreach generally.

In Gartner’s 2025 research into B2B buying preferences, 73% of buyers said they actively avoided suppliers who sent irrelevant outreach.

Now consider what happens when AI makes sending irrelevant outreach easier and cheaper than ever.

I don’t think it takes much imagination to see where that leads.

More Meetings Don’t Necessarily Mean More Opportunities

One of my biggest concerns about the growth of AI-powered outbound isn’t the technology itself. It’s how companies are measuring success.

There seems to be an increasing obsession with the volume of emails sent, responses generated and meetings booked.

But none of those things necessarily tells you whether a campaign is commercially successful.

I witnessed this problem with a SaaS client last year.

The company invested in an external GTM provider to generate outbound activity at scale. The campaigns were producing responses, but the quality of those responses and their relevance to the company’s ideal customer profile were questionable.

And because the company had invested money in generating those responses, pressure began building on the sales team to prioritise them.

Suddenly, a reply to an email could be interpreted as a promising lead, even if the buyer had expressed very little interest or wasn’t a particularly good fit.

I’ve seen the same fundamental problem many times throughout my career, long before AI existed.

Companies become so focused on generating leads that they forget to ask whether those leads are actually worth pursuing.

A response isn’t an opportunity. A booked meeting isn’t necessarily a qualified meeting. And a pipeline full of poorly qualified opportunities isn’t something to celebrate.

It’s potentially an expensive distraction.

This becomes particularly concerning when companies have already invested time and money into developing a refined ideal customer profile and target account strategy.

What’s the point of defining the companies most likely to buy from you if you’re then going to abandon those criteria whenever somebody responds to a mass outbound campaign?

I don’t believe high-volume prospecting is automatically wrong.

If you’re selling a relatively inexpensive solution with a short sales cycle, volume can be an entirely sensible part of your strategy.

Even with more complex sales, it’s possible to work with considerable volumes when your data is properly segmented and your targeting is accurate.

The problem arises when volume becomes a substitute for qualification.

The measure of a successful outbound campaign shouldn’t be how many people respond. It should be how many suitable opportunities eventually turn into revenue.

That means looking at the entire process, from the quality of the accounts being targeted to the conversion rates of meetings, opportunities and closed deals.

Otherwise, it’s remarkably easy to spend a lot of money creating more work for your sales team without creating much additional revenue.

B2B Buyers Are Changing, but They Still Need Salespeople

Another interesting development in 2026 is how AI is changing the way B2B buyers research and evaluate software.

I can relate to this personally.

When I’m considering buying a new piece of software, I’ll often start by asking ChatGPT or another AI assistant to recommend suitable products.

I’ll ask it about integrations, alternatives, reviews, pricing and the advantages or disadvantages of different solutions.

It’s incredibly convenient.

What previously involved visiting multiple websites, reading reviews and comparing product pages can now be done through a conversation.

And I’m certainly not alone.

According to G2’s 2026 Buyer Behavior Report, more than 80% of surveyed B2B software buyers had used AI chatbots to source software recommendations during the previous two years.

However, there’s something particularly interesting about what happens after that initial research.

G2 also found that 40% of buyers considered evaluation the longest stage of their buying journey.

AI may help buyers discover potential solutions faster, but they still need to gather evidence, assess risks and get agreement internally.

I also believe AI can sometimes add to that difficulty by giving buyers more options to assess.

There’s a well-known concept called the paradox of choice, where having too many options can make decision-making harder rather than easier.

I think we’re starting to see elements of that in B2B software buying.

AI can generate a list of alternatives within seconds, complete with comparisons and recommendations.

But the buyer still has to determine which information is reliable, which solution genuinely meets their requirements and whether the potential investment is justified.

And when many of those solutions appear to offer much the same thing, the decision becomes even more complicated.

This brings me to another observation about the SaaS industry.

Having spent much of my career selling software, I remember when new technology frequently offered capabilities that simply hadn’t been available before.

The innovation itself could be a compelling reason for buyers to pay attention.

Today, in many of the software categories I follow, I see far more products competing to replace existing solutions rather than introducing something fundamentally new.

That’s not to say innovation has stopped. It hasn’t.

But differentiation has become harder, particularly when every vendor is describing its latest AI features as revolutionary.

For salespeople, this means that simply presenting a new feature or claiming to have better technology often isn’t enough to create genuine interest.

They need to understand why a buyer would consider changing something that’s already working, or why a company that doesn’t currently use a particular solution should invest in one.

That requires good questioning, an understanding of buyer motives and the ability to challenge existing beliefs.

All fundamental sales skills.

Buyers Don’t Necessarily Want Fewer Salespeople. They Want Better Timing.

In May 2026, Gartner published research showing that 67% of B2B buyers preferred a sales rep-free buying experience.

At first glance, that might sound like terrible news for the sales profession.

However, the same research found that 69% preferred to validate AI-generated insights with a salesperson.

I don’t find those findings particularly contradictory.

I think buyers increasingly want to conduct their initial research without being interrupted by somebody trying to sell them something.

But when they’re seriously considering an investment, particularly one involving significant financial or operational risk, they still value speaking with somebody who understands the solution.

Consider the difference between buying a $50 monthly subscription and committing to software costing $50,000 a year.

With the cheaper product, you might be perfectly comfortable making the decision yourself. If it doesn’t work out, you can cancel.

With the more expensive solution, the consequences of making the wrong decision could be considerably greater.

You may need clarification around implementation, integrations, security, contract terms or whether the solution can genuinely deliver the outcomes being promised.

That’s where a capable salesperson can add value.

The distinction I think many companies are missing is that buyers don’t necessarily want to avoid salespeople.

They want to avoid dealing with salespeople before they’re ready.

And when they are ready, they want to deal with somebody who can provide useful information, answer difficult questions and help them make a confident decision.

Not somebody who simply repeats information they’ve already read on the website.

Being Known Before Buyers Are Ready Matters More Than Ever

If buyers are increasingly conducting their own research before engaging with salespeople, there’s another important question to consider.

How do you make sure your company is one of the options they consider?

This is where I think B2B sales and marketing need to become more closely aligned.

According to 6sense’s 2025 Buyer Experience Report, the winning vendor was already on the buyer’s initial shortlist in 95% of the purchases studied.

The research also found that buyers first contacted salespeople around 61% of the way through their buying journey.

Interestingly, that’s earlier than the 69% reported the previous year. One reason identified by the research was that buyers wanted help understanding the AI capabilities of potential vendors.

But the bigger lesson remains the same.

By the time buyers decide to engage with salespeople, they’ve often already formed strong opinions about which vendors they prefer.

That makes familiarity increasingly important.

I’ve always encouraged salespeople to think about outbound prospecting as something much broader than sending cold emails and asking for meetings.

A good outbound sequence should be a sequence of tasks, not simply a sequence of emails.

That might involve researching a target account, connecting with the appropriate buyer on LinkedIn, sending a short personalised message, making a phone call, sharing a relevant piece of information or engaging with something the buyer has published.

Not every interaction needs to contain a pitch.

In fact, I’d argue many shouldn’t.

The objective is to become familiar to the right people over time, so that when a genuine buying requirement emerges, your name or your company’s name is one they recognise.

This shouldn’t be confused with expecting every salesperson to become a full-time content creator.

I regularly see advice suggesting salespeople should publish on LinkedIn every day, build a personal brand and become recognised experts in their field.

There’s certainly value in doing that, but I don’t think it’s realistic for most salespeople who are already managing demanding full-cycle sales roles.

They have accounts to research, buyers to engage, meetings to conduct and opportunities to manage.

Building brand awareness should be a shared responsibility between sales and marketing, supported by a sensible prospecting strategy.

And as buyers increasingly use AI tools to discover potential vendors, marketing teams also need to think carefully about how their companies are represented in search results, reviews, independent content and AI-generated recommendations.

The important point is that sellers should stop treating every interaction as an immediate opportunity to book a meeting.

Sometimes the most valuable outcome from an interaction is simply that the buyer remembers you.

The Best Use of AI in Sales Isn’t Replacing the Salesperson

Despite my concerns about how AI is currently being used, I think it offers enormous potential for improving sales performance.

I just don’t believe the greatest opportunity is where much of the attention is currently focused.

Rather than trying to automate the entire sales process, I’d encourage companies to start by looking at the administrative work that consumes so much of a salesperson’s time.

Account research is an obvious example.

AI can help sellers monitor their target accounts, identify relevant developments, research industries and prepare useful summaries before meetings.

A salesperson working with 50 carefully selected accounts could receive regular updates about changes in leadership, company announcements or other developments that might influence buying decisions.

That’s valuable information which would previously have required considerable manual effort.

Call transcription and analysis are another excellent use.

A salesperson can use AI to summarise a meeting, identify the questions that were asked, review the commitments made and prepare for the next conversation.

Sales leaders can also use it to identify patterns across recorded calls and investigate where their teams may need additional coaching.

The important distinction is that AI should support professional judgement rather than replace it.

A transcript doesn’t necessarily capture everything that happened during a sales conversation. It may miss the wider context, the buyer’s motivations or information that was never discussed during the call.

And AI-generated feedback isn’t automatically correct simply because it sounds confident.

The same applies to CRM analysis.

AI can identify patterns in activity, pipeline progression and conversion rates, but those patterns still need to be interpreted by people who understand the company, its buyers and how it sells.

I think the biggest opportunity is to use AI to remove unnecessary administrative work, improve preparation and give salespeople more time to do the things that require genuine human judgement.

If we can achieve that, the technology will have delivered something worthwhile.

But if we simply use the time saved to send another ten thousand emails, I’m not convinced we’ve achieved very much at all.

My Predictions for B2B Sales in 2027

I don’t have a crystal ball, and I’m certainly not going to pretend I know exactly how this industry will develop.

However, based on what I’ve experienced during 2026, there are three developments I think are worth watching closely.

1. AI-Powered Outbound Will Get Worse Before It Gets Better

My first prediction is that the problems we’re currently experiencing with AI-generated prospecting will intensify during 2027.

The technology is still developing, and companies are still experimenting with how to use it.

Salespeople are under pressure to become more productive. Sales leaders are under pressure to generate pipeline. And technology providers are promising increasingly sophisticated automation.

I don’t see any immediate reason why that combination will result in less outbound activity.

Quite the opposite.

I expect more companies to adopt AI-powered prospecting, more sellers to automate their messaging and more emails to compete for the attention of the same buyers.

Eventually, I believe companies will become much better at understanding which applications of AI genuinely improve sales performance and which simply create unnecessary activity.

But I don’t think we’re there yet.

My concern is that we’ll spend another year making the same mistakes at greater speed and volume before enough companies start questioning whether the results justify the investment.

2. AI Could Change How Salespeople Build Target Account Lists

My second prediction is more speculative, but it’s something I’ve started noticing in the sales technology market.

Data providers are increasingly making their products accessible through conversational AI interfaces and integrations using the Model Context Protocol, or MCP.

For example, Apollo has introduced capabilities that allow users to search for contacts, research companies and build prospecting workflows through AI-powered interfaces.

You no longer necessarily need to navigate multiple filters and menus to find the data you want.

You can simply describe what you’re looking for.

In many ways, that’s a great development. It makes sophisticated tools easier to use and lowers the learning curve for salespeople.

However, I can see a potential problem.

Traditionally, building a target account list involves working through structured criteria. You define your target industries, company sizes, geographies, relevant characteristics and buyer personas.

You then evaluate the results and refine your criteria.

With conversational interfaces, I worry some salespeople will start skipping much of that discipline.

Instead of carefully constructing a list based on a well-defined ideal customer profile, they’ll simply ask an AI assistant to find thousands of companies that might benefit from their solution.

The system might produce a perfectly usable list, but that doesn’t mean the salesperson understands why those accounts were selected.

I can also see a commercial incentive for some technology providers to encourage this behaviour.

Many data platforms operate using credits, with certain activities such as accessing contact information, enrichment and AI research consuming those credits.

The easier those activities become, the more frequently customers may use them.

I’m not suggesting that’s necessarily the intention of every provider, or that conversational interfaces automatically consume more credits than traditional workflows.

But I do think it’s worth considering how these changes could affect both buying behaviour and costs.

My longer-term concern is whether some providers will eventually reduce their investment in traditional user interfaces as more customers migrate towards AI-driven workflows.

If that happens, carefully structured account research could become less accessible to the people who still prefer working directly with filters, lists and data.

And there’s a historical parallel here.

Ten or fifteen years ago, companies began giving salespeople access to marketing tools and CRM systems that made mass emailing incredibly easy.

Give a salesperson who’s struggling to hit target the ability to send a thousand emails at the click of a button, and many will use it.

Particularly when there’s no immediate consequence.

Eventually, email deliverability problems, spam filtering and damaged sender reputations forced companies to become more careful about how they used those tools.

I fear we’re repeating that cycle, only this time with much more powerful technology.

3. Companies Will Invest in AI Skills While Neglecting Sales Fundamentals

My third prediction concerns sales training.

I expect demand for training on AI tools and AI-assisted selling to continue growing throughout 2027.

That’s perfectly reasonable.

Salespeople need to understand how to use the technology available to them, just as they’ve had to learn how to use CRMs, sales engagement platforms and other tools throughout their careers.

But I also believe many companies will make the familiar mistake of treating the latest technology as the answer to their existing performance problems.

I’ve seen this happen repeatedly during more than two decades of training and coaching sales teams.

A company identifies a performance challenge, invests in something new and expects results to improve.

When those results don’t materialise, attention moves to the next initiative.

Meanwhile, the fundamental skill gaps remain.

The salesperson who struggles to ask meaningful discovery questions doesn’t suddenly become better at discovery because they’ve learnt how to prompt ChatGPT.

The account executive who can’t confidently challenge a senior stakeholder doesn’t develop that confidence simply because AI has prepared a detailed account briefing.

And the salesperson who consistently gives away discounts unnecessarily doesn’t become a better negotiator by automating their emails.

These are different skills.

AI can support them, but it doesn’t automatically replace the need to develop them.

There’s also the problem of reinforcement.

Companies sometimes assume they’ve already addressed a particular skill because they delivered a training programme several years ago.

But they may have failed to reinforce the learning, and half the team might have joined since the training took place.

In Salesforce’s 2026 State of Sales research, 46% of surveyed sales reps globally said they rarely received feedback on their sales conversations.

That concerns me far more than whether those salespeople have access to the latest AI prospecting tools.

Sales is a profession built on skills that need to be practised, reviewed and continuously improved.

I believe the best companies in 2027 will be those that develop their people’s ability to sell while teaching them how to use AI to support that ability.

Unfortunately, I suspect many others will continue investing more heavily in technology than in the people expected to use it.

What Sales Leaders Need to Do Differently in 2027

If I could give one piece of advice to sales leaders heading into 2027, it would be to stop allowing technology and short-term pressure to dictate their sales strategy.

I’ve met plenty of sales leaders who spend most of their working days buried in a CRM system or an Excel spreadsheet.

They’re often excellent at analysing data, producing reports and managing operational processes.

But managing a sales organisation requires more than understanding the numbers.

AI could make this problem worse.

Sales leaders can already use AI to analyse large volumes of activity data, review call recordings and investigate individual performance far more quickly than before.

That’s an enormous opportunity.

However, I worry that some leaders will simply spend more time interrogating their systems rather than using the information to improve their teams.

A report identifying poor conversion rates doesn’t solve anything.

The value comes from understanding why those conversions are poor and doing something about it.

That might mean reviewing call recordings with individual sellers, improving a qualification process, changing how inbound leads are prioritised or investing in B2B sales training to address specific weaknesses.

Technology should make sales leaders better coaches and decision-makers, not simply more efficient report writers.

But there’s another responsibility I think sales leaders need to take more seriously.

They need to become better at pushing back against unnecessary changes in direction.

I’ve seen companies spend considerable time and money developing new sales strategies, target account plans and positioning, only to abandon them a few weeks later because the results haven’t appeared quickly enough.

Sometimes the change comes from the CEO. Sometimes it’s the board. Sometimes it’s somebody returning from a conference with an exciting new idea.

Whatever the reason, constantly changing direction can destroy the consistency required to make a strategy work.

This is especially true for companies operating with longer sales cycles.

If your average deal takes six months to close, why would you expect a new prospecting strategy to demonstrate its full revenue impact after 45 days?

You might see early indicators. You might identify problems that need correcting.

But there’s a difference between improving the execution of a strategy and abandoning the strategy altogether.

I think sales leaders need to establish realistic expectations before launching major changes.

Agree on the objectives, the measures of progress and how long the company is prepared to commit before making a decision.

If the strategy is likely to require six months before meaningful revenue results appear, say so.

Don’t promise results in 60 days simply because that’s what somebody wants to hear.

And if senior leadership starts demanding another change after eight weeks, be prepared to challenge that decision.

Of course, I understand that pushing back against a CEO or board isn’t always comfortable.

There can be personal consequences.

But I’d also argue that if you’re working for a company that constantly changes direction, ignores realistic expectations and holds sales leaders accountable for impossible timelines, your long-term prospects there probably aren’t particularly good anyway.

You can either take the risk of challenging those decisions or continue accepting changes that you know are unlikely to succeed.

Personally, I’d rather have the difficult conversation.

Final Thoughts

I don’t think 2026 has been a particularly encouraging year for B2B sales, especially within the SaaS industry.

There’s been plenty of technological progress, but I’m not convinced we’ve seen an equivalent improvement in the quality of selling.

In some areas, I think the opposite has happened.

We’ve made it easier to produce more outbound activity, generate more content, collect more data and analyse more information.

But none of that guarantees better conversations, stronger opportunities or more revenue.

My prediction for 2027 is that this imbalance will continue before the industry eventually becomes more disciplined about how AI is used.

I also think there’s an opportunity here.

While many companies continue chasing the latest tools and trends, others can take a more measured approach.

They can invest in understanding their buyers, selecting the right accounts, developing their salespeople and building strategies they’re willing to stick with.

None of those things is particularly new or exciting.

But after 25 years in B2B sales, I’ve learnt that the fundamentals rarely change as much as people like to believe.

Technology will continue evolving, and salespeople will need to evolve with it.

I just hope we don’t become so obsessed with teaching salespeople how to use AI that we forget to teach them how to sell.

About the Author

I’m David Craig White, a British B2B sales trainer, coach and consultant with more than 20 years’ experience helping sales teams get results.

When I’m not writing B2B sales articles, I’m providing B2B sales training, coaching and sales consulting to B2B sales teams, sales leaders and business owners.

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