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CRM software systems were once the digital backbone of business growth, but what worked in the past doesn’t always fit the pace and pressure of today. In 2025, companies aren’t just seeking digital tools, they’re demanding agility, speed, and autonomy. And that’s exactly where legacy CRM systems are falling short.

A new wave of AI-native, no-code platforms is reshaping the industry, moving CRM from a rigid, IT-owned tool into a dynamic, business-controlled engine.

According to a recent Nucleus report, organizations shifting away from legacy vendors such as Salesforce in favor of modern no-code platforms are seeing significant improvements, including implementation times reduced by up to 70%, a 37% drop in total cost of ownership, and lead response times cut by more than 60%.

Here are five reasons why legacy CRMs are fast becoming obsolete, and why no-code is proving to be a promising, modern alternative.

1. Legacy CRMs can’t keep up with today’s speed of business

Businesses today operate in a state of perpetual change – new markets, new regulations, and new customer expectations. Yet many traditional CRMs, born in a different era, demand lengthy implementation cycles and code-heavy customization just to support basic adaptations.

In contrast, modern systems like no-code platforms are built on composable architectures that prioritize speed, flexibility, and business user autonomy. This allows organizations to configure and scale solutions rapidly without getting held back by complex, developer-led customization.

In fact, we’re seeing companies across core industries like manufacturing and financial services increasingly pivot to no-code models to avoid delays and spiraling costs.

It’s a clear signal that businesses are no longer willing to tolerate multi-year timelines to achieve meaningful outcomes. Adaptability and speed are no longer nice-to-haves, they’re essential for staying competitive.

2. AI and automation are now table stakes

Businesses now rely on AI to deliver personalized experiences, make smarter decisions, and streamline workflows. Yet many legacy CRM systems treat AI as an afterthought – a feature layered on top rather than embedded into the core of the platform.

Modern platforms, by contrast, are AI-native from the ground up. They use machine learning to automate lead routing, predict customer behavior, and optimize campaigns in real time. Organizations embracing these capabilities are seeing substantial improvements, such as a 61% reduction in lead generation response times and higher overall conversion rates.

Automating repetitive and manual tasks assist in giving teams back valuable time to focus on what truly matters, such as strategic thinking, creative problem-solving, and driving business growth.

3. The cost of complexity is unsustainable

Legacy CRMs often come with hidden costs: high developer overheads, third-party consulting fees, and expensive integrations that require constant maintenance. The burden on IT is immense, and the total cost of ownership (TCO) continues to climb long after deployment.

No-code platforms significantly lower these expenses, with firms reporting up to a 70% reduction in development costs and average savings of over $300,000 on external consultancy fees.

Newer no-code platforms remove many of these barriers by enabling configuration and updates without specialized technical knowledge. As a result, organizations are seeing a meaningful reduction in total cost of ownership. ROI is scrutinized more than ever, and the economic case for moving away from legacy tools is increasingly compelling.

4. Business teams demand control

Legacy CRM systems were designed with IT departments in mind, often requiring developer intervention for even simple changes. This creates bottlenecks and slows down innovation, particularly for departments like sales and marketing that need to move quickly and iterate on processes in real time.

No-code platforms are reversing this dynamic by giving control directly to business users. In fact, the number of citizen developers - non-technical employees empowered by no-code tools to build applications - is expected to rise by 50% this year.

With drag-and-drop interfaces, visual workflow designers, and intuitive configuration tools, non-technical staff can build and refine processes without needing to go through IT. This decentralized control fosters agility and allows organizations to respond to market shifts much faster.

5. Unified platforms drive real business agility

Legacy CRMs often operate in silos - disconnected systems for sales, marketing, service, and operations that struggle to communicate with one another. This fragmented approach creates inconsistent experiences and significant operational drag.

Modern no-code CRMs break down these barriers by unifying all functions within a single, cohesive platform. Shared data models, integrated workflows, and real-time visibility empower teams to collaborate seamlessly, respond faster to customer needs, and drive consistent outcomes.

With AI embedded throughout, this unification is key to enabling true business agility - not just reacting quickly, but aligning seamlessly across departments to deliver smarter, more cohesive customer experiences.

The no-code future is already here

The rise of no-code platforms marks a turning point in enterprise software. Rather than relying on rigid, IT-managed systems that require months of development and a deep bench of engineers, businesses now have access to tools that are fast, flexible, and accessible to all.

For organizations still tied to legacy CRM systems, the question is no longer if change is coming, it’s how quickly they can catch up. No-code isn’t just a trend. It’s a response to the urgent need for speed, adaptability, and user empowerment in the business environment.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

A function that was once buried deep within IT departments, cyber security is now firmly making its way up the boardroom agenda. 72% of UK businesses now classify cyber security as a high priority, with that extending to 96% of large businesses.

As recent high-profile breaches at M&S, Co-op and Harrods have shown, cyber resilience is now central not only to operational integrity but also to brand value, regulatory compliance and investor confidence.

Greater awareness has emerged as businesses shift from short-term solutions adopted during the pandemic to long-term, strategic partnerships with specialist cyber security providers. Increasingly, organizations recognize that cyber security requires an integrated approach involving continuous monitoring and proactive risk management.

The growing complexity and specificity of cyber threats mean that a bespoke, tailored approach is necessary, driving demand for advisory-led solutions delivered by experienced, security-cleared professionals.

That shift in perception is now being reflected in dealmaking. In the second quarter of 2025, the UK cyber market saw a flurry of M&A activity, much of it led by private equity platforms executing bolt-on acquisitions. These transactions may not always grab headlines, but they are sending a clear signal - cyber security is a strategic growth priority.

A new kind of risk

The cyber threat landscape has evolved. Today’s attacks are more frequent, more sophisticated and more damaging. The recent incidents involving the “Scattered Spider” group are just the latest reminder of the long-term impact these attacks can have, beyond the legal and financial consequences, but to customer trust and brand reputation. That’s why boardrooms are starting to reassess their cyber readiness.

In sectors such as public services, infrastructure and education - where the risks of failure are especially high - strong cyber defenses are no longer optional.

In addition, the rapid advancement of AI will accelerate cybersecurity risks, as it lowers the barrier for executing sophisticated attacks and enables threat actors to automate, scale, and personalize their tactics with unprecedented precision.

Regulation is raising the stakes

At the same time, government regulation is putting company directors firmly on the hook. The UK’s proposed Cyber Security and Resilience Bill will make senior executives directly accountable for managing cyber risks and ensuring operational resilience, bringing the UK closer to European frameworks like the NIS2 Directive and DORA.

This is changing how cyber security is viewed at the top. It’s not just about ticking boxes or passing audits. It is now a central part of good governance. For investors, strong cyber capabilities are becoming a mark of well-run companies. For acquirers, it’s becoming a critical filter for M&A, particularly when dealing with businesses that hold sensitive data or operate critical systems.

This regulatory push is part of a broader global shift towards greater accountability. In response, businesses are increasingly adopting governance models that embed cyber risk management into their strategic decision-making processes. Boards that fail to adapt not only risk regulatory penalties but also stand to lose investor confidence and market competitiveness.

Private Equity steps in

While overall deal values are still below long-term trends, deal volumes are rising. In Q2 alone, there were 114 cyber-related deals across Europe and North America, well above average. In the UK, activity is particularly strong in the small to mid-sized market, with private equity firms at the forefront.

Cyber security is a highly fragmented mission critical sector with strong recurring revenues, sticky customer relationships and a compelling margin profile. In an environment where investors are increasingly focused on resilience over growth, these are attractive attributes.

From product to partnership

The post-Covid shakeout is also playing a role. Many companies quickly adopted off-the-shelf solutions during the pandemic to meet urgent needs. Today, with greater familiarity and a clearer understanding of risk, boards are opting for more tailored, enterprise-grade services.

This is not just about technology, there is a growing premium on advisory-led solutions. Highly qualified, security-cleared professionals providing bespoke assessments and continuous monitoring. In other words, clients want expertise and service, not just software.

From a valuation perspective, this matters. While public market multiples continue to fluctuate, exposed to macro shifts such as US tariff announcements earlier this year, premium valuations continue to cluster around providers with diversified offerings and deep client integration. As PE buyers weigh bolt-ons and platforms, these traits are driving acquisition rationale.

Players need to stay ahead

The forces pushing cyber up the corporate agenda aren’t going away. Threat actors are growing bolder, regulators are getting tougher and the risks remain high.

The result is a market in transition. What began as a compliance arms race is evolving into a sophisticated, services-led ecosystem. For dealmakers, this creates opportunity but also demands discernment. Not every cyber asset will command a premium.

The winners will be those with deep expertise, defensible margins and client relationships that extend beyond the server room.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Hyper-personalized AI is transforming the workplace. Unlike standard automation, it works by learning from individual user behaviors, allowing businesses to tailor interactions on a much more human level. Not only does it help businesses to streamline their operations, it also drives efficiency while enhancing the user experience.

For employees, AI can suggest ways to improve productivity, automate repetitive tasks and provide real-time insights based on their work habits. In contact centers, for example, it can escalate intuitively from an AI Agent to a call with a human if it's a nuanced or complex problem.

While in retail, AI-powered assistants make personalized recommendations and offer timely discounts based on past interactions, purchasing history and market trends, which can result in impromptu purchases. It allows customers to feel like they are being listened to – and that their previous purchases are appreciated.

And it is this increasingly natural and ‘human’ experience that is helping to redefine what a digital brand interaction looks and feels like. The impact cannot be ignored.

According to Gartner, businesses investing in hyper-personalization are experiencing an uptick of 16% in commercial outcomes. The ability of AI to refine and improve interactions in real-time makes it a valuable tool for business growth. But as AI becomes more embedded – as it becomes smarter and more human – there are concerns over the impact this might have on privacy and security.

Ensuring privacy and security

After all, the very nature of hyper-personalized AI presents a paradox. The more an AI system knows about an individual, the better its recommendations. But this has led to some people raising concerns over issues such as surveillance, consent and the potential misuse of data.

It’s one of the biggest question marks still hovering over the issue of continuous learning. And without proper governance, AI may retain sensitive information, increasing the risk of unauthorized access, data breaches and regulatory non-compliance.

Thankfully, high-profile regulations such as GDPR and California Consumer Privacy Act (CCPA) frameworks already impose strict rules on data handling, and businesses failing to comply face not just legal repercussions but also reputational damage. But, that hasn’t stopped some people from pursuing AI-specific legislation – such as the AI Act in the EU – to provide specific protection.

There’s also an ethical dimension. Poorly designed AI can inadvertently reinforce biases or expose personal details that should remain confidential. If employees and customers lose trust in AI systems, companies will struggle to gain the full benefits of hyper-personalization. To thrive, organizations need to harness the power of AI while ensuring that privacy isn’t compromised.

How businesses can balance AI innovation with privacy

The good news is that businesses don’t have to choose between AI-driven efficiency and data privacy – they can have both. The solution lies in embedding privacy-first, responsible AI principles into frameworks and strategies from the outset. Here’s how:

Anchor core, long-lasting principles: Build ethical, trustworthy AI systems by prioritizing transparency, inclusiveness, and ongoing monitoring to foster trust and drive lasting value.

Establish robust governance: Define clear policies, conduct risk assessments, and assign dedicated roles to ensure compliance and ethical AI practices.

Ensure data integrity: Use high-quality, unbiased data to deliver fair and accurate AI outcomes across all user groups.

Adhere to compliance needs: Proactively address tightening regulations with strong governance and data protection to mitigate legal risks.

Test and monitor consistently: Conduct regular testing and continuous monitoring to align AI with ethical standards and performance goals.

Optimize tools effectively: Leverage advanced platform features like retrieval mechanisms and feedback loops to enhance transparency and ethical behavior.

Human oversight and participation is also part of the puzzle in optimizing and building trust in AI. At key points in AI workflows, humans help ensure accuracy and reliability. For example, in Agentic Workflows, AI breaks tasks into smaller steps and handles repetitive work, while humans review important decisions before final actions are taken.

AI then continuously learns from human input, improving over time. This approach combines the speed and efficiency of AI with the judgment and experience of human workers to create a system that is not only faster but also more reliable and adaptable.

In other words, with the right safeguards – and the right leadership and employee engagement strategy to ensure these protocols are followed – businesses can unlock the full potential of hyper-personalized AI without compromising security or trust.

The future of AI and privacy: staying ahead of the curve

What’s more, businesses that integrate privacy-first thinking into their AI strategies are likely to be the ones that thrive in the long run. The key is to build a governance framework that not only meets regulatory standards but also fosters trust among employees and customers.

One of the first steps is ensuring AI tools are rigorously assessed before deployment. That means evaluating how data is being processed, stored and used. It would also help to run pilot programs to help iron out privacy concerns and identify risks before full-scale implementation.

From the beginning, you need to work with a trusted provider to define and configure algorithms to prevent unintended biases and ensure fairness across different user groups at every level, whether it's an LLM, agent or App. AI should also be designed to evolve responsibly, integrating smoothly into workflows while maintaining strong privacy protections.

Clear visibility

Observability and traceability are crucial. Not only should people have clear visibility into how AI makes decisions, they should also be able to challenge or verify AI-generated outputs with real-time tracing, explainable AI decision paths and thought streaming.

Organizations should also be actively monitoring and optimizing AI agent performance with comprehensive analytics that track the likes of latency, workflow success, and operational efficiency. Adopting such an approach would help to build confidence while reducing the risk of AI being perceived as a black box.

Finally, we must never forget who has the final word. AI should be an enabler, not a replacement for human expertise. Organizations that combine AI’s analytical capabilities with human judgment will be better positioned to innovate while maintaining ethical and privacy standards.

There’s a lot to take in. But one thing is clear. Hyper-personalized AI presents enormous opportunities for businesses. But it comes with responsibilities. Work with vendors with a responsible AI framework and platform that ensure robust tools and embedded ethical considerations for meticulous data curation, rigorous model testing, ongoing transparency, and continuous monitoring and adaptation of AI systems.

The result then becomes not just compliance but also enhanced user trust and exceptional experiences, setting the stage for pioneering a future where AI is a trusted ally.

We feature the best employee management software.

This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Here are hints and the answers for the NYT Connections: Sports Edition puzzle for Aug. 25, No. 336

Immigration has become a political flashpoint as countries across the West try to cope with an influx of migrants seeking a better life.

(Image credit: Ben Birchall)

Here are the answers for The New York Times Mini Crossword for Aug. 25.