Luiz Domingos, the Chief Technology Officer and Head of Large Enterprise R&D at Mitel, has built a distinguished profession spanning over 20 years. Known for his progressive approach and deep technical expertise, Luiz has consistently delivered high-quality solutions in enterprise communication, contact center systems, network management, and cloud services.
In his current role at Mitel, Luiz sets the strategic direction for technology, emphasizing innovation and reliability. He leads the introduction of cutting-edge technologies and ensures the corporate’s portfolio stays on the forefront of the industry. Before joining Mitel, Luiz served as Chief Product and Technology Officer at Unify, where he successfully managed all the product portfolio and spearheaded the event of disruptive cloud offerings.
Mitel is a worldwide leader in business communications, providing a comprehensive range of solutions that empower organizations to attach, collaborate, and serve their customers more effectively. Offering the whole lot from on-premises systems to cloud-based communication platforms, Mitel delivers reliable, scalable, and progressive products that address the various needs of companies of all sizes. With a deal with seamless integration and a commitment to high-quality user experiences, Mitel helps corporations stay connected and competitive in today’s rapidly evolving workplace environments.
Many corporations still depend on legacy communication tools. Out of your perspective, what are the most important obstacles that outdated systems present to businesses today?
Many corporations depend on outdated Private Branch Exchange (PBX) systems, contact centers, and fragmented collaboration tools. Using legacy tools reminiscent of these can result in a scarcity of integration and interoperability, as they operate with closed architectures and lack proper SW interfaces. This makes integrating with modern AI-driven solutions, CRM platforms, and cloud-based applications much harder.
When organizations use fragmented, legacy tools, user experience (UX) and productivity can suffer as application implementations usually are not adapted to modern, flexible work modes – distant, office, or mobile – and don’t provide omnichannel capabilities. Moreover, when too many outdated systems are used, security risks develop into heightened, resulting in increased vulnerabilities and compliance gaps as a result of evolving data protection regulations like GDPR. Finally, these legacy tools also cause higher product maintenance and repair or operational costs, increasing the full cost of ownership.
How do these communication bottlenecks impact a corporation’s ability to implement AI-driven solutions effectively?
AI applications depend on real-time data availability, seamless integration across multiple media channels, and automation mechanisms. Nevertheless, legacy systems are likely to store data in internal proprietary formats that AI cannot access or tap into, which impairs AI’s true potential and, in some cases, results in fragmentation. To operate appropriately, AI requires each structured and unstructured data. Since legacy systems’ data structures usually are not conducive to that approach, these systems limit AI’s ability to research conversations, extract business value, and personalize communication activity.
Moreover, many AI-driven applications, reminiscent of sentiment evaluation and speech-to-text, depend on real-time analytics. Outdated infrastructure often lacks the processing power and real-time connectivity needed for such applications, resulting in latency and inefficiencies inside a business. True AI-driven automation – virtual assistants, workflow automation, etc. – requires deep integration with communication platforms. Often used legacy systems with outdated or missing API support create barriers and bottlenecks to integration and further hinder automation capabilities.
Addressing these communication bottlenecks might help organizations unlock the complete potential of AI-driven solutions, improving efficiency, decision-making, and UX.
How does Mitel approach communication system modernization for big enterprises transitioning from legacy systems?
Mitel takes a strategic, hybrid approach to modernizing unified communications (UC) tools, helping enterprises transition from their legacy systems. Relatively than enforcing a full overhaul, Mitel advocates for and offers hybrid solutions composed of on-premise applications and personal and public cloud solutions with full interoperability. This hybrid model integrates telephony infrastructure, SBC/gateway equipment on the network’s edge, UC applications, and cloud-based collaboration apps, allowing enterprises to modernize at their very own pace.
As an answer orchestrator, Mitel focuses on creating the crucial integrations and services across all customer-deployed applications. Key principles guiding this approach include:
- Hybrid Cloud Deployments – Relatively than an entire rip-and-replace approach, Mitel maintains and updates existing on-premise and personal cloud PBX/UC/Contact Centers while integrating modern collaboration tools in the general public cloud, ensuring enterprises can evolve without major disruptions.
- APIs and SDKs – Mitel consistently updates and develops APIs and SDKs to bridge the gap between legacy systems and modern applications in collaboration, CRM, and ERP environments. This flexibility allows businesses to steadily adopt recent services without causing major disruptions to their day by day operations.
- AI Integration with Legacy Systems – Mitel enhances existing communication platforms with AI-driven capabilities reminiscent of visual voice mails, virtual assistants/agents, and real-time transcription. These AI functions work with cloud LLMs and likewise leverage small language models (SLMs) that could be operated without major infrastructure investment or upgrades.
- Security & Compliance-Driven Upgrades – Mitel prioritizes security and regulatory compliance, implementing security standards reminiscent of end-to-end payload and signaling encryption and data encryption at rest. It certifies all products to comply with the most recent regulations in certain industries and regional laws and regulations.
AI is transforming business communication. What do you see as the following major advancements in AI-driven unified communication systems?
AI is getting used to remodel UC systems by enhancing efficiency, automating tasks, and improving enterprise communications. It is usually getting used to strengthen security. Things reminiscent of user authentication with voiceprint, continuous vulnerability assessments, and system security auditing contribute to stronger protection measures for enterprises.
At the identical time, Agentic AI and virtual assistants are expanding. Organizations are enhancing these AI-powered assistants with multi-modal abilities that support various communication functions, including handling complex queries, automating responses, assisting with scheduling, and knowledge retrieval.
AI can be driving innovations in voice-to-text capabilities, real-time multilingual translations, and sentiment evaluation. These enhancements profit Contact Centers by improving worker productivity and overall user satisfaction.
Moreover, using GenAI for content management is rising as LLMs are being integrated to generate analytics reports, summaries, legal and compliant records, etc. We’ll proceed to see more AI adoption to drive the UC space as enterprises use AI-driven language models to prepare, retrieve, and share enterprise knowledge to enhance collaboration and data-sharing optimization across organizations.
How is Mitel preparing for the rise of AI-powered virtual assistants, automation, and predictive analytics in workplace communication?
Mitel began its AI journey several years before the arrival of LLMs, and we proceed to integrate AI into our product and technology partnerships. When applicable, we incorporate AI capabilities into our portfolio to reinforce customer solutions, with a powerful deal with agentic AI, including Virtual Assistants and Virtual Contact Center Agents. Moreover, Mitel offers AI capabilities reminiscent of natural language processing (NLP), call and meeting analytics, system analytics and predictive reporting, and low code/no-code workflow automation, which all streamline UC and Contact Center applications.
How is Mitel leveraging AI and enormous language models (LLMs) to reinforce communication and collaboration for enterprises?
Mitel leverages AI and LLMs to enhance the general communications and collaboration experience inside an enterprise. As mentioned earlier, Mitel integrates AI and LLM capabilities into its products, leveraging advanced speech and text evaluation (specifically NLP and speech-to-text), intelligent virtual assistants with context memory, and task automation. Mitel can be offering an answer for self-help and customer support with AI, incorporating the shopper knowledge base via an AI model training process. These technologies enhance real-time communication, optimize customer interactions, ensure system security, and supply cost-effective, 24/7 monitoring and support.
What are the most important challenges in integrating LLMs into enterprise communication systems, and the way is Mitel addressing them?
There are just a few challenges relating to integrating LLMs into enterprise communication systems, including data privacy, security, latency, and the necessity for flexible AI integration. As a worldwide organization, data privacy concerns and regulatory compliance (GDPR and the European AI Act) are our top priorities. So, we’re ensuring our AI solutions protect customer data in any respect costs. For enhanced security, Mitel is investigating the usage of SLMs deployed at the shopper’s network edge to limit and protect data that may very well be exposed to public cloud LLMs. In hybrid cloud environments, it’s imperative that each one products have the correct interfaces/APIs to include AI safely and securely. Mitel has modernized its products to enable AI integrations across on-premise, hosted, and personal and public clouds. We’re also developing flexible workflow creation capabilities that can allow a “bring your individual LLM” (BYO-LLM) approach to avoid vendor lock-in.
Modern communication requires LLM responses to be instantaneous for real-time collaboration tools like voice and video, which creates infrastructure challenges. Mitel’s vision is to depend on Edge AI to process real-time communication and reduce latency for a natural experience and interaction with AI assistants. Finally, Mitel is working on AI models that could be fine-tuned for specific industries like healthcare, finance, and hospitality, ensuring more vertically relevant and context-aware AI-driven communication.
By way of AI-powered natural language processing, what applications are you most enthusiastic about inside Mitel’s product ecosystem?
Given the measurable and immediate return on investment, Mitel Contact Center is essentially the most exciting area for AI-driven LLM and NLP solutions. The AI-powered virtual agents with chat and speech interaction can handle customer inquiries and gather information before escalating to a live agent, reducing workload and improving response times. Features reminiscent of call recordings with transcription, summarization for compliance, sentiment analytics for customer satisfaction, and agent training all improve operations. Mitel’s UC solutions include visual voicemail, smart search, knowledge management, and noise cancellation for clearer calls.
As AI reshapes communication, how should businesses approach the moral considerations of AI-driven workplace interactions?
AI is significantly transforming workplace communication and collaboration, introducing recent user and customer experiences. Nevertheless, these changes don’t come without ethical challenges. Ethical considerations needs to be consistently addressed at every stage of AI implementation, including training AI models on diverse datasets to avoid bias and ensure fair decision-making. Certainly one of the most important concerns with AI is transparency and explainability, which requires clear terms and conditions and disclosure of AI use. Using AI should expand human augmentation and empowerment, but it surely is just not a alternative.
Moreover, security and AI misuse prevention needs to be considered to guard against deepfakes and manipulation of user data and credentials.
What steps can organizations take to make sure a smooth transition for workers as AI becomes more embedded in day by day workflows?
Enterprises must take steps to foster adoption, trust, and productivity to make sure a smooth transition to AI-based solutions. Step one for organizations is to create AI policies and enterprise governance to define AI’s role inside the company after which persist with them. Leadership also needs to align on messaging and advocacy for AI adoption and offer training to all employees on how AI works, its limitations, and the best way to use it effectively.
Concurrently, organizations should introduce AI collaboration tools and integration frameworks that empower employees with AI assistance to reinforce the decision-making process while maintaining human oversight. Leadership also needs to address ethical and job security concerns and supply channels to collect worker feedback and measure the incremental value introduced by AI.
By doing all these items early within the AI adoption process, employees will feel more confident using the tools, and organizations will see a faster ROI on their investments.
