Artificial intelligence (AI) is no longer a key differentiator for businesses – it has become an imperative. The technology has evolved at such breakneck pace over the last 12 months that what is cutting edge today quickly becomes dated, with its depth of capabilities growing by the day.
But rather than just having AI for the sake of it, companies need to work with their channel partners to carefully consider what solutions will work best for them and their end customers.
So what are the most effective AI solutions available in the Channel? How can organisations best use the technology? What are the key challenges and opportunities in deploying, using and maintaining AI? And what future applications can the technology be used for?
Chris Angus, VP for CX expansion at 8×8, said 2025 marked the defining moment when AI moved from being a proof-of-concept to a solution that’s now being put in place. In that respect, he said it has stopped being merely a feature and started becoming a foundational layer of operations, particularly in contact centres.
“We saw customers move from fragmented tech stacks to streamlined platforms where AI is embedded directly into routing, transcription and post-call analytics,” said Angus. “That’s the new table stakes. This alignment across data, infrastructure and workflow unlocked huge gains in agent performance and service quality. We’re not talking about AI as an accessory anymore: it’s become a core utility.”
Ben Merrills, CTO, Jola, said, “2025 was the year AI became truly operational across the Channel. Resellers and MSPs shifted from experimentation to deploying AI in core workflows, and vendors focused on packaging AI into predictable, repeatable services. A major development was the rise of contextualised AI, designed to work with clean, structured data rather than ungoverned models.
“This trend shaped Jola’s approach to its AI Reporting Engine in Mobile Manager, which uses predefined prompts and exported datasets to deliver secure, consistent and reliable reporting.”
Andrew Platt, managing director, Infinitel, added, “In 2025, AI in the Channel moved from experimental add-ons to practical, built-in capability. Communications and collaboration platforms introduced new AI features such as smarter call routing, automated transcription, real-time language support and more advanced analytics.
“These developments made AI far more accessible to MSPs and resellers, allowing them to deliver meaningful improvements without the cost or complexity previously associated with AI deployment.”
AI options
With so many different AI solutions out there, it’s hard to know where to begin. A good starting point is to first determine exactly what it’s needed for and how it will be applied, looking for technology that’s both quick and easy to configure.
“There’s a lot of noise in the Channel right now with many AI solutions looking shiny but not scaling or integrating well,” said 8×8’s Angus. “What’s cutting through are tools like AI-driven quality assurance, intelligent routing, sentiment analysis and post-call summarisation, especially when they’re part of a unified platform, not bolted-on extras.
“You want AI capabilities embedded into the agent experience: real-time assistance, smart escalation, transcription with context. Partners and customers are telling us what they want most is simplicity and reliability: not piecemeal tools, but one ecosystem that just works.”
Among the most in-demand technologies, said Infinitel’s Platt, are AI-enhanced communications, service desk automation and analytics. Many platforms, he said, now include features such as intelligent call handling, multilingual support, automated note-taking, searchable transcripts and sentiment insights.
“MSPs are taking these building blocks and creating packaged services that help customers improve operational efficiency and customer service,” said Platt.
Phil Alton, sales director, Node 4, said, “The broad spectrum of AI capabilities range from the relatively easy to deploy – embedded AI within cloud and SaaS platforms, especially around CX, to more advanced security tools that use AI for threat detection, or data platforms that cleanse, govern and interpret.”
Jeff Green, co-founder and CEO, Elisha Telecom, added, “Our partners commonly deploy transcription and summarisation tools, autonomous call-handling systems, multilingual voicebots, knowledge-based chat agents, and analytics engines capable of interpreting sentiment and intent.
“And while many CCaaS platforms already include AI-driven quality assurance, reporting and performance monitoring, the unifying hesitancy we’re hearing from partners is compatibility as business leaders are increasingly choosing to prefer AI layers that enhance their existing PBX or UCaaS estate rather than replace it.”
With a saturation of low and no-code AI toolsets available that make automation far more accessible, James Cadman, chief customer officer, Luware, said that partners can help organisations create bespoke agents, designed to solve specific operational problems without data scientists or large integration projects.
This democratisation, he said, was particularly impactful for small and medium-sized enterprises, who can now access meaningful AI capabilities without large investment.
“Alongside this, AI-assisted employee tools, from sentiment tracking and knowledge surfacing to automated interaction logging, have become mainstream,” said Cadman.
He added, “On the customer-facing side, generative AI has matured significantly, allowing virtual agents to handle entire journeys that feel more conversational and natural. The Channel is also seeing rapid uptake in AI-led compliance and risk technologies, especially for regulated industries that require deep oversight across voice, chat and digital channels.”
Key benefits
AI essentially enables businesses to enhance their decision-making, streamline operations and improve customer experience, according to Jola’s Merrills.
Using structured data and controlled prompts, he said that the technology can automate reporting, highlight risks and identify opportunities with a high degree of accuracy, resulting in significant efficiency gains, better service levels and clearer visibility of performance, especially when it’s embedded directly into existing workflows.
Hilary Oliver, CCO of Tollring, said organisations can use AI to uncover patterns in their customer interactions, operations and workflows that were previously invisible or too time-consuming to find. Instead of manually reviewing call recordings, she said that teams are now able to check sentiment and conversation content, ask clear questions and receive a meaningful answer.
“By applying AI-driven analytics to the thousands of conversations that agents have every week, companies can reveal where agents are consistently struggling or doing well, and show exactly where discussions are becoming repetitive, strained or unresolved,” said Oliver. “This can lead to changes in process, policy or coaching plans. For example, it can detect where back office processes are causing unnecessary repeat calls, point to the root causes and help organisations streamline those processes so customers no longer need to chase for updates.
“In a similar way, AI can reduce average call-handling times by identifying the handful of questions customers ask most often and allowing businesses to create more effective FAQs or support materials for agents. It can also highlight emerging sales opportunities by examining customer feedback content and sentiment, and identifying unmet needs within specific segments.
“What is clear is that many organisations are still unaware that they are sitting on a mine of untapped intelligence hidden away in conversations, meetings and chats. AI is making that intelligence more accessible than ever.”
EPOS AI is a prime example of how voice pickup technology is used to create an optimised audio experience. Used along with adaptive active noise cancellation, Jessica Harrison, sales director, EPOS (UK and Ireland), said that it provides high quality clarity on both sides of the call.
“By interacting with advanced beamforming microphones and noise reduction algorithms, this system enables the device to automatically adapt to a user’s speech while analysing their sound environment,” said Harrison.
In a video conferencing context, AI can be used to make meeting room experiences more natural, smoother and easier to use, according to Holli Hullet, co-founder at Boom Collaboration. In that respect, it can be used to do everything from room design and installation to transcribing and summarising meetings.
“In multi-camera environments, software can often outperform manual camera operators, especially when organisations don’t have staff dedicated to controlling PTZ devices,” said Hullet. “It also reduces the risk of human error. While AI has quietly supported the VC industry for years, think face tracking or sound zoning – it is rapidly becoming more sophisticated.”
Rather than being a solution in itself, 8×8’s Angus said that AI improves other technologies, systems and processes by reducing friction, and speeding up and improving insight. In the contact centre, for example, he said that means automating repetitive admin, predicting what customers want and helping agents make smarter decisions quicker.
“We’ve seen organisations cut call handling time and reduce support volumes by up to 40 per cent – not by cutting headcount, but by reinvesting that time into better service,” said Angus. “Agents want this. They want smart tools that help them focus on high-value interactions. When implemented correctly, AI doesn’t just make the work faster. Instead it makes it more human.”
Implementation challenges
One of the biggest barriers to AI implementation is the existing infrastructure and data. The problem is that many companies still use disconnected legacy systems and/or poor quality data.
“AI depends on accurate, well-structured information, and many organisations still operate with fragmented datasets,” said Jola’s Merrills. “Trust and security are also key concerns, as unguided AI can behave unpredictably without proper safeguards. Jola’s approach addresses this through predefined prompts, controlled inputs and auditable processes that ensure reliability.”
Another hurdle is resistance to change. To overcome that, organisations need to get buy-in from employees from the start in order to instil a change culture.
“The biggest challenge remains organisational readiness,” said Luware’s Cadman. “Many businesses have acquired AI-enabled tools but haven’t established the processes, governance or training required to use them effectively. As a result, AI often becomes shelfware rather than something embedded into everyday workflows. Successful deployment increasingly depends on supporting teams who can help those who need guidance in understanding how AI can complement their work rather than disrupt it.
“Integration also plays a major role. AI generates the most value when it can draw on clean, concerted data. Organisations working with fragmented communication platforms or legacy systems often find that potential benefits are constrained by their underlying infrastructure. On top of this, there is growing pressure to ensure AI systems are deployed responsibly. Without clear governance, organisations risk cultural issues as much as compliance exposure.”
Rob Quickenden, CTO, Cisilion, added, “Deploying AI at scale is not simply plug-and-play. Organisations face infrastructure complexity, as AI workloads demand high-performance compute, low-latency networking and scalable storage.
“Cisco stats show that less than 15 per cent of global organisations believe their networks can support widescale AI workloads without major upgrades, while Microsoft stresses the need for resilient architectures across hybrid and multi-cloud environments.
“These challenges extend to integration – embedding AI into existing workflows without disrupting operations requires careful planning and orchestration. Networks designed for pre-AI workloads need an upgrade.”
Finding the right partner
It’s also vital to work with a technology partner whose solution integrates smoothly and performs reliably, said Tolling’s Oliver. It should also be accurate and secure, she said.
“While many conversation intelligence tools now exceed human accuracy, some still struggle with accents, jargon or poor-quality audio, so careful evaluation is essential,” said Oliver. “At the same time, robust security and strong data governance are critical to ensure sensitive customer interactions are protected and compliant.”
Richard Brown, co-founder and managing director, Converse360, advised, “Build a roadmap, but start small and build without trying to take on too much too quickly. Businesses need to seek relationships with vendors and resellers who will help by removing the jargon and identifying genuine use cases where AI can help – and then use their expertise to design, launch and ensure business value is realised.”
In Platt of Infinitel’s view, the main challenges are ensuring that data is managed correctly, helping teams adapt to new workflows and maintaining the quality of AI outputs over time. Given that AI tools rely on accurate information and appropriate permissions to work effectively, he said that MSPs play an important role in configuring these systems, training users and monitoring performance so businesses get reliable, long-term value from their investment.
“The key for a reseller is to understand and educate their customers about how AI can positively impact their particular industry or business,” said Adam Geldard-Williams, partner account manager, Evolve IP. “They need to tailor conversations rather than just deploying a generic mindset about what AI can do.
“It needs to be relevant. How should they be using and maintaining their solutions? The technology is always evolving. Businesses also need to remember to continuously feed AI technology with relevant information because the solution is only as good as the data inputted.”
Future applications
The number of applications that AI can be used for is almost limitless. From enhancing voice and messaging capabilities to video conferencing, the boundaries are being pushed every day.
“Looking ahead, we expect AI to play a larger role in real-time support during calls and meetings, surface relevant information automatically during customer interactions and help identify operational issues before they escalate,” said Infinitel’s Platt. “As AI models become more controllable and better suited to regulated environments, adoption will increase across sectors that have previously been cautious. For MSPs, this will create opportunities to deliver more proactive, insight-driven services.”
In terms of specific technologies, Martin Saunders, COO at Highlight, said that future applications are likely to centre on agentic AI. For example, he said that using data from the Highlight Service Assurance platform, an autonomous agent can be used to continuously monitor multi-tenant performance data, predict emerging service-level agreement (SLA) violations for specific customers, and suggest adjusted bandwidth policies or raise targeted tickets with remediation suggestions before end users notice any degradation.
“AI can enhance and extend a team’s capability, taking over continuous, high-frequency loops, such as SLA tracking or relevant ticket generation, while human operators remain the strategic authority,” said Saunders. “In this model, network engineers shift from manual execution to high-level supervision, making sure that the agent’s output aligns with business intent, much like a senior manager reviewing the work of an essentially unlimited pool of junior engineers within established guardrails.”
In a customer experience (CX) context, Luware’s Cadman said that AI will increasingly condense complex patterns, trends and behaviours into insights that team leaders can use instantly to improve service and performance.
Added to that, Cadman said, as models become more sophisticated and integrate more deeply with business systems, AI will handle a larger share of complete end-to-end customer journeys, enabling them to focus on high-impact scenarios where empathy and strategic thinking matter most.
Tollring’s Oliver added, “Significant transformation still lies ahead. No longer limited to static dashboards or generic reports, future analytics will use AI to surface personalised, actionable insights tailored to each user.
“Capabilities such as natural language query, agentic AI and adaptive intelligence will anticipate what users need to know based on their role, their industry and their daily patterns, automatically telling them what matters, in a way that drives better decisions and stronger outcomes.”
Gavin Jones, director, wholesale partners, BT Wholesale, said, “In 2026, AI will accelerate partner revenue growth further with portfolios expanded with AI-driven tools. Expect to see AI-driven cybersecurity, voice AI and AI-based network optimisation become more commonplace as partners unlock future-proof workflows for customers.
“However, for companies to fully embrace AI-driven solutions, they require the right combination of network infrastructure, security and seamlessness of deployment.
“That means they need channel partners that provide them with secure fixed and mobile connectivity as the backbone of AI deployment, including full fibre broadband and 5G nationwide coverage, and deliver ongoing wraparound services to turn AI into a tangible asset that delivers transformative potential.”
This market report was included in our January 2026 print issue. You can read the magazine in full here.
