Avainsana: Google Cloud

The Best of Google: Agentspace

Google’s novel combination of AI tools promises to illuminate the entire organization, from HR to marketing and from sales to software development

In this blog series, we talked to two seasoned IT and data professionals, Codento’s very own SVP Markku “Pulu” Pulkkinen and Google Cloud’s Ted Schönbeck, about the upcoming transformation marked by Google’s newest AI innovation, Agentspace. 

Businesses have long been digging their way out from data silos towards a shining vision of “collective brilliance.” In our previous blog, we delved into the persistent issue of data silos and the challenges they cause in all parts of the organization. We also explored Markku’s decades-spanning journey in enterprise data management and introduced Google’s newest AI innovation, Agentspace, which promises to revolutionize how enterprises harness their data.

Now, let’s dive deeper into how Google Agentspace aims to deliver on its pledge of collective brilliance across the organization.

Value for All from the Best of Google

According to Google Cloud’s Nordic CTO, Ted Schönbeck, Agentspace’s innovativeness lies in bringing together the best of Google. Firstly, it acts as a centralized, company-branded access point for information, featuring over 100 built-in connectors to various systems and Google’s enterprise search capabilities. Secondly, NotebookLM, Google’s AI-powered research and writing tool, enables users to synthesize complex information by creating notebooks and chats from up to 100 sources. Additionally, NotebookLM can generate remarkably natural-sounding AI podcasts from any data. Thirdly, Agentspace provides a platform for rapidly developing autonomous AI agents tailored to diverse enterprise functions, from HR and creative teams to finance and strategy.

A prevalent challenge in AI deployment is the risk of hallucinations, wherein AI systems generate inaccurate or misleading information. According to Ted Schönbeck, Agentspace directly addresses this through a dual-pronged strategy. Firstly, it leverages the advanced reasoning capabilities of Google’s Gemini AI, coupled with Google-quality search and comprehensive enterprise data integration. In his recent LinkedIn post, Ted quoted a benchmark study where Gemini 2.0 clearly beat the competition in the amount of hallucinations. Secondly, Agentspace mitigates the inherent risk of hallucination associated with general large language models by grounding its AI within the specific context of your enterprise data. This focused approach ensures significantly enhanced accuracy and reliability, minimizing the potential for extraneous data correlation.

When we asked about the sweet-spot customer segments, Ted elaborates on Agentspace, currently available in early access preview for selected clients: “Agentspace excels in complex data environments. Its technology-agnostic architecture, seamlessly integrating with platforms like Microsoft, Google, and Salesforce, ideally suits large enterprises with heterogeneous data ecosystems.” Furthermore, Ted continues that Agentspace’s value proposition extends from large corporations to smaller, agile organizations. “I have been discussing with many digital-native startups, who have been extremely interested. Such organizations, able to move fast, can achieve rapid implementation and immediate operational benefits,” he envisions.

A key strategic advantage of Agentspace is its modular deployment model. Organizations can adopt functionalities incrementally, beginning with readily available solutions like NotebookLM Enterprise. This phased approach allows for tailored implementation and optimized resource allocation, ensuring a seamless integration aligned with specific business objectives.

Illuminate Every Function of Your Enterprise

At Codento, a Finnish Google Cloud Premier Partner, we deliver AI-powered solutions to Nordic customers. Our team’s expertise and innovation commitment position us as the strategic partner for organizations seeking to maximize their data-driven potential.

According to Ted Schönbeck and Markku Pulkkinen, the transformative power of AI technologies, exemplified by solutions like Agentspace, will revolutionize operational efficiency across all organizational functions. As we envision, Agentspace will serve as a critical intelligence layer, illuminating enterprise-wide insights.

In the past couple of years, working with Google Cloud AI, we at Codento have already witnessed success with our Google-Cloud-based HR AI Agent, which automates routine tasks and frees up valuable time for HR leaders and individuals while ensuring data privacy and security. Agentspace represents the next evolution of AI-driven optimization. Beyond streamlined HR data management, it empowers us to deliver strategic value to key stakeholders, such as Chief HR Officers. We are developing solutions that address organizational needs proactively, automate complex workflows, and provide data-backed decision support. While doing all this, Agentspace ensures transparency through source document attribution, mitigating the risk of AI-generated inaccuracies.

In our customers’ sales functions, we can finally realize the vision of the sales representative getting a tailor-made, easy-listening podcast that includes a full recap of customer developments, industry events, and the latest company solution updates. Agentspace will enable every star seller to stay informed, enhance customer relationships, and drive innovation that combines customer insights, market data, and the organization’s intellectual property.

For our clients’ marketing teams, Agentspace will empower actionable insights into end-customer preferences without requiring an in-depth understanding of every product development feature. Marketers can focus on analyzing customer data and trends, delivering valuable feedback to engineering teams, and ensuring that product innovations align with market demands and customer needs.

Software teams, in turn, can automate their engineering processes, proactively fix bugs and vulnerabilities before they occur, and optimize codebases using data-driven insights. Agentspace facilitates more efficient workflows, higher-quality software, and faster delivery times, ultimately enhancing the overall development lifecycle and product reliability.

Let People Excel at What They Do Best

Overall, Google Agentspace promises to finally break down the data silos. It does this by combining the unmatched search capabilities of Google, the novel ways of interacting with data through NotebookLM tools, and the endless opportunities for building fit-for-purpose AI agents for any use case one can think of.

Technology as such, however, does not change anything. As Google’s Ted Schönbeck nicely frames it: “Partners like Codento play a crucial role in helping customers get the most out of Agentspace. Our partners’ role is not just about building and making the platform  work, but especially helping organizations really adopt the solutions to their everyday lives – helping with the transformation, as that is what it is.”

Ted also emphasizes that Agentspace, like AI in general, is not about getting rid of your people: “Humans don’t compete with AI, but rather with other humans using AI,” he concludes, “Agentspace frees people to do what people are the best at.”

Ted Schönbeck is Google Cloud’s Nordic CTO. He has more than 20 years of experience in IT, with companies like IBM, Dell, VMware, and Red Hat. Ted is a passionate cloud, digital transformation, and AI evangelist and a frequent event speaker.

Markku Pulkkinen, SVP at Codento, leads Google Cloud partnerships and business development, drawing on 25+ years at Microsoft and Oracle. He’s a proven leader in public cloud adoption, focused on driving productivity and potential through technology.

Breaking Down Data Silos with Google Agentspace

Will Agentspace finally unlock “collective brilliance”?

We talked to two seasoned IT and data professionals, Codento’s very own Markku “Pulu” Pulkkinen and Google Cloud’s Ted Schönbeck, about the upcoming transformation marked by Google’s newest AI innovation, Agentspace. Let’s hear what they have on their minds.

“For decades within leading American technology organizations, I’ve observed the persistent challenge of fragmented data and its impact on operational effectiveness,” explains Markku Pulkkinen, Codento’s Senior Vice President and continues: “I’ve seen the promises, the hype, and the inevitable disappointment when challenges related to shared organizational knowledge persist and data silos remain. Despite advancements in enterprise data management, the promise of unified organizational knowledge remains largely unrealized.”

According to Markku, examples of data challenges in key organizational functions include:

• Human Resources: Inefficient data aggregation hinders efficient employee management and prevents the automation of critical administrative processes.
• Sales: Suboptimal lead management and the absence of real-time, actionable insights limit the ability to personalize sales strategies and drive revenue growth.
• Marketing: Inability to extract meaningful campaign performance data and inefficient content management processes hold back targeted marketing efforts and ROI optimization.
• Software Development: Excessive time spent on bug detection, code optimization, and compliance adherence diverts resources from strategic innovation and makes development work mind-numbing.

Persistent data silos inevitably cause operational inefficiencies and block the ability to leverage collective organizational intelligence in every organization. However, Google Cloud’s most recent AI innovation, Agentspace, promises to address these challenges effectively and deliver on the promise of a truly integrated and efficient enterprise. 

Two Decades of Not-so-collective Brilliance

Some two decades ago, the pursuit of Markku Pulkkinen and his colleagues to connect data repositories at a leading database provider revealed the limitations of siloed data strategies. “The solutions of that day could often only partially solve the business problem,” Markku explains. “Subsequently, the industry pivoted towards collaborative platforms and CRM solutions, recognizing the strategic advantage of leveraging collective intelligence and actionable insights from sales data.” According to Markku, this evolution underscored the critical role of interconnectedness and collaboration in driving business success. “However, reflecting on my time at another tech giant back then, despite the best of intentions, we were nowhere near breaking down the data silos within the sales function, let alone across the entire organization.”

Over the years, Markku’s journey in enterprise data has been like peeling an onion: you reveal the complexities of seamless data integration layer by layer. In his own words, it has frequently resembled a Whac-A-Mole game, with new issues constantly appearing. A few years back, Markku moved from the offices of global giants to Codento, a leading Nordic Google Cloud Premier Partner. Therefore, he is now excited to see that it is time for Google Agentspace to step into the data silos game. 

As the other guru we had the pleasure to interview, Google Cloud’s Nordic Chief Technology Officer, Ted Schönbeck, puts it: “Agentspace is about unlocking your organization’s collective brilliance, providing an abstraction layer on top of AI that makes it incredibly simple for the average user to harness its power.”

Agentspace: A Collection of the Best of Google

Google Cloud’s Agentspace promises Enterprise AI spiced up with Google’s search capabilities. Skeptics might say, “Here we go again!” However, this time we think it comes with a new twist.

Ted from Google summarizes the three main points of Agentspace as follows:

• Search, i.e., any information available across the enterprise

With Agentspace, the days of siloed search and inconsistent AI agent experiences should be over. It offers a unified platform for information discovery regardless of the underlying technologies, breaking down barriers between teams and departments. For any organization, it’s like a single, company-branded “portal” with more than 100 ready integrations and Google-grade search capabilities across the enterprise.

1. NotebookLM, i.e., entirely new ways to interact with data

We’ve all wasted productive time looking for documents, data, and answers in the company intranet or other data sources. Agentspace introduces new ways to interact with any data. As Ted puts it: “NotebookLM is much more than just its cool feature of creating a podcast from any of your datasets. It is about building a library of notebooks or chatbots on all the topics that are important to you. For example, you could collect your 100 most important product briefs into a single chat, making it easy to interact with them whenever you need.” 

1. Expert Agents, i.e., Automate any business function

Agentspace includes pre-built expert AI agents to streamline tasks like data analysis, content generation, and customer support. It is also a platform for creating custom expert agents tailored to fit unique workflows, proprietary data sources, or business processes. Agentspace addresses the challenge of controlling enterprise data sharing by adhering to any complex structure of access hierarchies, thereby enforcing proper access control. Your tireless assistants only have keys to the doors they should have.

The Data Transformation Finally at Your Doorstep

“As I look to the coming months and years in IT,” says Markku Pulkkinen, “the possibilities of Google Agentspace are fascinating – even for a seasoned, slightly cynical tech trooper like me.”

Agentspace stands out due to its independence from any specific technology stack. It allows seamless integration with your existing systems, such as Microsoft Teams, Slack, Jira, or Google Workspace. It harnesses Google’s substantial investments and expertise in search and AI, ensuring top-tier performance and an unforeseen experience when interacting with data. The solution’s modularity means you can start with a reasonable upfront investment and scale as needed. Furthermore, the insights provided by Agentspace are highly reliable, as they are grounded solely in your enterprise data.

Ted Schönbeck is Google Cloud’s Nordic CTO. He has more than 20 years of experience in IT, with companies like IBM, Dell, VMware, and Red Hat. Ted is a passionate cloud, digital transformation, and AI evangelist and a frequent event speaker.

Markku Pulkkinen, SVP at Codento, leads Google Cloud partnerships and business development, drawing on 25+ years at Microsoft and Oracle. He’s a proven leader in public cloud adoption, focused on driving productivity and potential through technology.

Please stay tuned for our next blog that reveals more about the functionality of Agentspace, Ted Schönbeck’s and Markku Pulkkinen’s viewpoints about the future, and how we at Codento see each of your organization’s above-mentioned functions benefit from this emerging innovation from Google.

Decoding the Consultant Life: Real stories from real consultants

Olli Alm, Senior Software Engineer, about working for our customer Smartvatten

I am Perttu Pakkanen and my interest as Codento’s talent acquisition lead is to better articulate why consulting could be a great career choice.

When potential customers ponder whether they should use our services, they usually like to see some reference cases. Why wouldn’t our potential employees think the same?

So, I had a chat with our Senior Software Engineer, Olli Alm. Olli has been working with our customer Smartvatten for their water efficiency technology. They are leading experts in the field in Northern Europe, helping their customers save hundreds of millions of liters of water every year.

I asked Olli to sit down with me in our office’s meeting room on a Tuesday afternoon. The weather outside was a bit rainy and dim, but it didn’t slow us down.

Here we go:

What kind of solution have you built?

I’ve worked on building a system for leakage monitoring and water consumption measurement, utilizing GCP infrastructure.

The client’s system is a water metering solution with two main functionalities: measuring water consumption and sending alerts, for example, in the case of leaks. What makes this particularly interesting is that it’s an IoT system, which means we’re constantly also dealing with hardware solutions and how they indirectly influence the larger system.

What I find fascinating is the challenge of keeping the whole system cohesive and building a unified architecture. In the IoT world, there’s an abundance of real-time data coming in from various countries and time zones, which raises unique challenges like efficiency, data accuracy, and synchronization.

The solution indeed seems like a unique one. What kind of tasks have you done in the project?

My work has been primarily focused on data-oriented back-end development, though I’ve also contributed to some front-end work.

On the social side, I interact daily with the client across multiple levels, including product owners, the CTO, and a smaller stakeholder team. The collaboration has been so close that I can confidently say that we have a good sense of trust with the client.

I’ve also been heavily involved in architectural work, which has been both challenging and rewarding.

Why I’ve enjoyed this project: The relationship with the client is very good and straightforward. There’s no unjustified pressure, communication is easy, and mutual trust makes it a pleasant working environment. I feel like an important part of the project and can see the impact of my work.

Those are good qualities in a working environment. What has been the most interesting thing you have done working for the customer?

One highlight has been working with time-series data and developing robust data pipelines. I also enjoyed contributing to the overall system architecture to make it more stable and efficient. Both aspects required creative problem-solving and provided a lot of professional growth.

What brings enthusiasm to your workdays?

There’s a constant but manageable level of pressure, which keeps things exciting without being overwhelming. Every day brings new and unexpected challenges – there’s always something fresh to tackle, which ensures I never get bored.

My days are usually quite busy, with a mix of maintenance tasks and new development work. The diversity of tasks keeps things engaging. Occasionally, there are urgent issues that require immediate attention, but that’s part of the fun.

Over time, I’ve learned so much that I can now work far more efficiently. It’s rewarding to see how much I’ve grown professionally through this experience.

What has been the most difficult part?

In general, learning to deal with uncertainty has been a big takeaway for me. It’s something I’ve improved at significantly during my time as a consultant.

A reflection on consulting: Consulting is like a marathon. Building a strong trust relationship with a client over the years allows the work to flow more smoothly. But occasionally, you’re faced with tough problems that take time to solve. The longer you work with the same client, the more efficient and effective you become.

What have you learned?

Working on a small team means the range of tasks I’ve handled has been extremely broad – from building infrastructure to fixing UI bugs. This has helped me develop a wide skill set.

Over the past three years, I’ve worked with Google Cloud Platform every single day, which has allowed me to deepen my expertise significantly. I’ve also refined my skills in routines, documentation, code quality, best practices, and multitasking, often juggling multiple responsibilities simultaneously.

It’s hard to point to one specific thing I’ve learned because the experience has been so comprehensive. However, I’d highlight Clojure as an interesting element – it’s something I’ve enjoyed exploring and using in this project.

That’s a lot of learning! Any last words to wrap things up?

In this project, my tasks have been very self-guided, which is a typical aspect of working on a small team. I appreciate the responsibility that comes with the role and enjoy the freedom to make my own decisions. This autonomy enhances my sense of self-efficacy and allows me to express my capabilities fully.

Codento fosters a professional environment with a strong emphasis on trust and responsibility, allowing me to thrive and deliver quality results in my daily work.

(We then continued to talk about different stuff not related to the subject per se and ended up using almost an hour for this. This was a great talk and I also learned a lot.)

—

Being part of pioneering projects like this allows for both personal and professional development. I strongly feel that at Codento you can engage in work that is not only challenging but also highly impactful in many industries.

Read more about us from our career site and see if there are any suitable opportunities for you and connect with us on our recruitment system!

About the interviewee:

Olli Alm is a Senior Software Engineer at Codento. He has 20 years of experience in different software development and architecture positions as well as teaching and research.

About the interviewer:

Perttu Pakkanen is responsible for talent acquisition at Codento. Perttu wants to make sure that the employees enjoy themselves at Codento because it makes his job much easier.

People, stop misusing Kubernetes!

Unless you have a viable use case like edge computing

Author: Jari Timonen, Lead Cloud Architect

No matter what color of gift paper you wrap it in, Kubernetes is complex and costly.

Initially, Google developed the predecessor of Kubernetes and named it Borg. Since then, Google has open-sourced the technology to benefit the broader community and to advance the state-of-the-art in container cluster management. And just like Google envisioned, Kubernetes has become a crucial part of modern container orchestration. Virtually everything in Google’s own environments, for example, runs as a container, managed with Kubernetes. To me, this seems like solid proof of Kubernetes’ reliability and scalability for huge corporations like Google.

But seriously, how many companies in the Nordics are Google, or even come close?

The fact, namely, remains that moving from virtual machines to containers and Kubernetes is a big investment. Therefore, this step just isn’t for most companies and organizations. I am concerned that there are countless companies whose business comes closer to “man and dog” than that of the global cloud giants, which are spending their time playing with Kubernetes.

How many companies in the Nordics are Google?

However, one viable use case for Kubernetes is emerging: edge computing. As our CTO Markku Tuomala wrote in his recent blog, edge computing – processing data closer to its source – offers big benefits in terms of latency, bandwidth, and efficiency for large industrial companies, telecom operators, and electricity providers.

Justifying Kubernetes: Edge computing

In the otherwise fast-changing world of industrial technology, edge computing has been annoyingly “just around the corner” for years. Things are about to change, however, since a number of very handy technologies from Google are making the orchestration of Kubernetes clusters more achievable. In this blog, I will share my experiences on how GKE, GKE Enterprise, and Anthos can revolutionize edge computing for industries that need very low-latency online services.

Google Kubernetes Engine (GKE) is Google’s managed Kubernetes service. It’s a robust solution for building and managing the capabilities needed for edge computing. Anthos, in turn, extends GKE to manage Kubernetes clusters across multi-cloud and hybrid environments. GKE Enterprise, the newest addition to the mix of solutions, allows Kubernetes clusters to be managed in a multitenant architecture, across clouds and on-premises environments, eliminating the need for extra servers. Google Distributed Cloud, finally, combines software and hardware to provide a fully integrated system. Such an integrated system supports edge computing scenarios, among others.

A standout feature of GKE is its team management capabilities. GKE allows the distribution of clusters and assigning specific teams to manage them. For example, team members in different locations—Pertti in Seinäjoki and Petra in Stockholm—can be given access and control from the cloud, eliminating manual interventions. This centralized control ensures all necessary tools and permissions are included in the package, simplifying operations significantly.

In edge computing scenarios, GKE offers unmatched ease of management. For example, updating a cluster can be as simple as making one change and deploying it across the network. This ease of operation is crucial for environments where Kubernetes management and updates are usually difficult. For instance, the North American Major League Baseball, uses Anthos to host applications like real-time game analytics, which need to run locally in the park for performance reasons.

Telia and Codento lead the way to Edge as a Service

Over the past two years, Codento’s team has pioneered using GKE and GKE Enterprise for edge computing. I am proud to say that we have achieved something no one else in the world has yet.

Our journey with Nordic telecom giant Telia began 2.5 years ago. Telia wanted to maximize the return on their 5G network investments beyond only speed. They also wanted to test Anthos’s capabilities in multi-cluster management.

Significant improvements in multi-cluster management.

Our joint efforts have been successful. Significant improvements in multi-cluster management reduced the time needed to run system upgrades from weeks to the minute it requires to change one configuration number. The first pilot customer is already using Telia’s platform.

Eye on the ball – Kubernetes can add or dilute value

Despite its advantages, Kubernetes is still complex and costly, often rightfully seen as a last resort. Managing multiple Kubernetes clusters is labor-intensive and expensive, so it is usually for organizations with strong technology know-how and advanced cloud environments.

Today, however, the burden of management and monitoring is much lower, allowing teams to focus on innovation and growth. GKE Enterprise, with its robust features and ease of multitenant environment management, will in my opinion be a game-changer for large industrial companies and service providers looking to harness the power of edge computing. By simplifying cluster operations and offering centralized control, GKE Enterprise enables businesses – specifically the businesses that have the needed maturity to lead modern cloud teams – to deploy and manage edge computing capabilities efficiently.

When all these prerequisites are fulfilled, Kubernetes will stop being a value destroyer that sucks time and energy and become a driver of innovation and operational excellence.

Key takeaways:

1. Google Kubernetes Engine (GKE), GKE Enterprise, Anthos, and Google Distributed Cloud offer a comprehensive solution for managing Kubernetes clusters across different environments.
2. Kubernetes has traditionally been seen as costly and complex , but these technologies make it more accessible, enabling advanced solutions like edge computing.
3. With GKE Enterprise, telecom players like Telia already offer their customers multitenant edge computing services based on Kubernetes clusters.

About the author:

Jari Timonen, is an experienced software professional with more than 20 years of experience in the IT field. Jari’s passion is to build bridges between the business and the technical teams, where he has worked in his previous position at Cargotec, for example. At Codento, he is at his element in piloting customers towards future-compatible cloud and hybrid cloud environments.

Stay tuned for more detailed information and examples of the use cases! If you need more information about specific scenarios or want to schedule a free workshop to explore the opportunities in your organization, feel free to reach out to us.

Boosting Contact Center Effectiveness with AI

Conversational AI happens at competitors’ CCs while you’re busy making other plans

Author: Janne Flinck, Data & AI Lead

Working for Nordic organizations in various industries, I have gladly noted that front-runners are already deploying modern Artificial Intelligence tools to increase their contact center efficiency and customer satisfaction. In contrast, the majority are still looking for marginal improvements via tweaks in ticket handling or streamlining the edges of their onboarding processes.

“Life is what happens to you while you’re busy making other plans.” This familiar motto applies to many Nordic customer service and contact center decision-makers regarding conversational AI: It’s happening at competitors’ contact centers while you’re reading this blog.

Exceeding customer expectations while managing costs

Whether you’re a Nordic public sector entity or a private company running your business here, exceptional customer service is crucial. According to Salesforce, nearly 90% of customers today perceive the experience delivered as important as the actual products or services. Customer service leaders and marketing and sales officers face a common challenge: providing consistent, high-quality service while managing costs and resources effectively.

Nearly 90% of customers perceive the experience delivered as important as the products or services.

You want to ensure prompt, accurate responses to customers within acceptable wait times, regardless of the time of day. Simultaneously, you must balance the cost of contact center teams and onboarding new agents. You want to stay agile and be able to scale to meet the needs of growing organizations or seasonal peaks. Moreover, you want to gain insights into customer behavior and service performance to steer strategic decisions for optimizing operations and improving service quality. This is where Google’s Customer Engagement Suite comes into play.

Agents for agents

Generative and conversational AI agents are revolutionizing customer service, particularly in contact centers. Customer Engagement Suite is a collection of Google Cloud products designed to enhance contact center agent productivity, boost customer satisfaction, and reduce operational costs.

When your agent starts a call with a customer, Customer Engagement Suite provides live transcription, real-time answers to the customers’ questions, and a discussion summary. This helps the agent focus on customer interactions without worrying about taking notes. Customer Engagement Suite’s omnichannel support covers chat, SMS, VoIP, and video, ensuring seamless customer experiences across all channels.

Generative AI agents produce automated answers to customers’ questions by integrating to enterprise knowledge bases and other internal and external data sources. Customer Engagement Suite can also automate tasks like checking order status or updating payment details, ensuring customers always receive up-to-date information and services tailored to their needs. All this increases the efficiency of operations, and we have seen customers reduce call durations by up to 10%, yielding a significant payback to the system investment.

We have seen up to 10% reductions in call duration.

Quick access to relevant agent data will also shorten the time needed for new employee onboarding. When newcomers have speedier access to appropriate knowledge, the onboarding period can be up to 25% shorter, leading to a stark improvement in efficiency.

Many customer service calls involve tedious information-seeking, often for questions that repeat over time. Customer Engagement Suite’s virtual agent chatbots can relieve your agents of the repetitive burden by automatically finding answers to common questions using existing information sources and handling text, voice, and images in customer encounters. By reducing the need for human intervention in routine cases, the chatbots free human service agents to offer a more personal and richer interaction that increases customer and employee satisfaction.

Customer Engagement Suite offers powerful analytics tools that provide insights into customer interactions. These tools help your organization identify trends, improve processes, and make data-driven decisions.

As the Customer Engagement Suite is fully developed and managed by Google, it allows you to concentrate on extracting value for your operations. The deployments are efficient due to its seamless integration with telephony and contact center applications and tools for building custom features that adapt to your processes.

The Quantified Impact of AI in Contact Centers

In the bigger picture, AI will affect both new hires and existing employees in the coming years—in both negative and positive ways, depending on your position. In Metrigy’s AI for Business Success 2024-25 global research study of 697 companies, the following was discovered:

• New hires – More than half of companies were able to reduce the number of new agents they needed to hire. The numbers are substantial: Those who did not use AI in their contact center, had to hire almost twice the number of agents during the year 2023 compared to those who used AI.
• Existing employees – When contact centers were augmented with AI, nearly 40% of companies were able to reduce their headcount, with the average reduction being about one in every four employees.

For business leaders looking for technology to drive cost efficiencies, AI is doing its job. For example, with the addition of AI agent assist, the average handle time dropped by an average of 30%. At the same time, each supervisor saves nearly two hours per week when AI helps with scheduling and capacity planning. In addition to making agents and supervisors more efficient, AI-enabled self-service also helps automate customer interactions so that fewer of them even require live agent attention.

Real-world success stories in the making

I am honored to help several of our leading customers in the Nordics embrace the benefits of generative AI and conversational AI in their contact center operations. The most value can be extracted in organizations where the number of daily contacts is high, and the onboarding cost is noticeable due to complex product structures. Such fields include retail, travel and leisure, banking, and insurance. Similarly, organizations with high peak demand, such as nonprofits with surging inquiries during a fundraising campaign or public offices with specific deadlines for citizens’ input, could benefit from Customer Engagement Suite. It helps diminish the burden of agents on duty, channels routine questions directly to virtual agents, and makes onboarding seasonal employees more straightforward.

As an experienced and awarded Google Cloud Solutions integrator, Codento offers comprehensive support to ensure a smooth transition to your contact center’s era of AI. The fact that Customer Engagement Suite is a complete solution developed and managed by Google will ensure a robust platform integrated with all your relevant data sources and a foreseeable future roadmap on which to build your contact center success.

Key takeaways:

1. The experience delivered, e.g., by your contact center agents is as important for your business as the product or service you actually sell
2. Google has packaged Artificial Intelligence tools for excellent customer service into a managed solution called Customer Engagement Suite
3. The efficiency effect of AI in Contact Centers has already been quantified and, e.g., handling times have been seen to drop by 30%
4. Codento is already working with Nordic organizations to harness AI for better customer experience and more efficient Contact Center operations

About the author:

About the author: Janne Flinck is an AI & Data Lead at Codento. Janne joined Codento from Accenture 2022 with extensive experience in Google Cloud Platform, Data Science, and Data Engineering. His interests are in creating and architecting data-intensive applications and tooling. Janne has three professional certifications in Google Cloud and a Master’s Degree in Economics.

Stay tuned for more detailed information and examples of the use cases! If you need more information about specific scenarios or want to schedule a free workshop to explore the opportunities in your organization, feel free to reach out to us.