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AI

AI startups raised over $5bn venture capital funding in 2022
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The rapid advancement of artificial intelligence (AI) has captured the attention of venture capital (VC) investors globally. Against this backdrop, 3,198 AI startups received $52.1 billion funding across 3,396 VC funding deals during 2022.

However, an analysis of GlobalData’s Financial Deals Database reveals that 2022 experienced a subdued VC funding activity across sectors and AI space also felt the brunt of a dent in investor sentiments. Although VC funding deal volume as well as value in the AI space declined in 2022 compared to the previous year, the impact was more prominent in terms of value.

Aurojyoti Bose, Lead Analyst at GlobalData, explained: “The number of VC funding deals announced in AI space globally declined by 4% in 2022 compared to the previous year, whereas the corresponding deals value was down by a massive 41.8%.”

AI deal volume experienced a fluctuating quarter-on quarter (Q-o-Q) trend throughout 2021 and 2022. Meanwhile, deal value declined for the six straight quarters through Q3 2022. However, there was a rebound in both VC funding deals volume and value in Q4 2022.

Some of the notable VC deals announced in the AI space during 2022 include $1.5 billion fundraising by Anduril Industries, $580 million raised by Anthropic, and $500 million fundraising by Black Sesame Intelligent Technology.

Bose concluded: “The subdued VC funding activity in the AI space seems to be for short-term while long-term prospects are likely to be promising and the rebound in both deals volume and value in Q4 2022 could be seen as an indication of it.”

ChatGPT, WebAssembly, and Serverless will spur app modernisation this year
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DevOps will be a dominant driver in the cloud computing arena in 2023, as enterprises advance their app modernisation strategies using the likes of ChatGPT and other AI-driven tech.

This prediction came about as part of research by GlobalData Technology Analyst Charlotte Dunlap, who notes that significant innovations in sophisticated application architectures will usher in new serverless deployment integrations with various cloud services, abstracting complicated configuration requirements.

Dunlap said: “Ground-breaking new artificial intelligence (AI) chatbot achievements based on large language models (such as ChatGPT) will ease developers’ cumbersome coding requirements by automating the writing/converting of scripting, particularly programming languages developers are unfamiliar with.

GlobalData reveals that increased AI/automation advancements and accessibility will significantly escalate in 2023, playing a greater role in easing next-generation app development capabilities among developers and DevOps teams.

Dunlap added: “A primary example that highlights 2023 AI/automation innovations is the recent release of ChatGPT, version 3.5. The Natural Language Processing (NLP) model, developed by OpenAI, is trained on a massive amount of text data, so it’s able to generate human-like text and response. In addition to using the prototype AI chatbot to outright create new code without having to know any programming languages, a major use case will be in improving the Natural Language Understanding (NLU) of apps targeting customer service to provide more human-like responses to user-inputs. Such technology advancements will result in a newfound prioritization of DevOps among enterprises, based on a new wave of developer technologies, which significantly remove obstructions hindering deployment of modern apps.”

Additionally, over the next 12 months, developers will have access to integrated serverless app deployment options through key services including database management and app development tools, paving the way for serverless computing to be paired with event-driven architectures.

Dunlap conlcuded: “Since its rollout a few years ago, serverless computing hasn’t lived up to expectations due to the problematic underlying architecture. However, in recent months, providers have worked through some of those issues, including abstracting scalability configuration requirements.

Furthermore, game-changing developer tools, including WebAssembly, will leverage traditional web browser technology to create new uses with containers and Functions-as-a-Service (FaaS). The new technology is able to provide more robust cloud management of apps at scale on the same cloud infrastructure.’’

Conversational AI will reduce contact centre agent staff costs by $80bn in 2026
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Conversational artificial intelligence (AI) deployments within contact centres will reduce agent staff costs by $80 billion by 2026, according to Gartner.

Furthermore, worldwide end-user spending on conversational AI solutions within contact centres is forecast to reach $1.99 billion in 2022.

“Gartner estimates that there are approximately 17 million contact center agents worldwide today,” said Daniel O’Connell, VP analyst at Gartner. “Many organizations are challenged by agent staff shortages and the need to curtail labor expenses, which can represent up to 95% of contact center costs. Conversational AI makes agents more efficient and effective, while also improving the customer experience.”

Gartner projects that one in 10 agent interactions will be automated by 2026, an increase from an estimated 1.6% of interactions today that are automated using AI. Conversational AI can automate all or part of a contact center customer interaction through both voice and digital channels, through voicebots or chatbots, and it is expected to have transformational benefits to customer service and support organizations within two years.

“While automating a full interaction – also known as call containment or deflection – corresponds to significant cost savings, there is also value in partial containment, such as automating the identification of a customer’s name, policy number and reason for calling. Capturing this information using AI could reduce up to a third of the interaction time that would typically be supported by a human agent,” said O’Connell.

While the benefits of conversational AI are compelling, the technology is still maturing. A fragmented vendor landscape and complexity of deployments will result in measured adoption through the next two years.

“Implementing conversational AI requires expensive professional resources in areas such as data analytics, knowledge graphs and natural language understanding,” said O’Connell. “Once built, the conversational AI capabilities must be continuously supported, updated and maintained, resulting in additional costs.”

Complex, large-scale conversational AI deployments can take multiple years as more call flows are built out and existing call flows are fine-tuned for improvement. Gartner estimates integration pricing at $1,000 to $1,500 per conversational AI agent, though some organizations cite costs of up to $2,000 per agent. Therefore, early adoption of conversational AI will be primarily led by organizations with 2,500 or more agents with budget for the requisite technical resources.

Data literacy to be most in-demand skill by 2030
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Just one quarter of employees believe their employer is preparing them for a more data-oriented and automated workplace (25%), including in the marketing industry.

That’s according to new research from analytics provider Qlik, despite most business leaders predicting an upheaval in working practices due to the rapid onset of artificial intelligence (AI).

With 32% of employees surveyed reporting they had changed jobs in the last 12 months because their employer wasn’t offering enough upskilling and training opportunities, there is a stark need to better upskill workforces to support the workplace transition that is already underway.

The report, Data Literacy: The Upskilling Evolution, was developed by Qlik in partnership with The Future Labs and combines insights from expert interviews with surveys from over 1,200 global C-level executives and 6,000 employees.

The findings, which were largely consistent across all geographies surveyed, reveal how the rapid growth in data usage is extending enterprise aspirations for its potential and, in turn, transforming working practices. As organisations shift from passive data consumption toward a state of Active Intelligence, where continuous data becomes integrated into working practices to trigger immediate actions, the report predicts how this will impact skills requirements and professional opportunities.

Data literacy: The most in-demand skill in the future workplace

The study found that business leaders and employees alike predict that data literacy – defined as the ability to read, work with, analyze and communicate with data – will be the most in-demand skill by 2030. And 81% of executives believe it will become as vital in the future as the ability to use a computer is today.

This reflects the greater appreciation of data in the enterprise. Global employees surveyed report their use of data and its importance in decision-making has doubled over the past year. While 86% of executives now expect all team members to be able to explain how data has informed their decisions.

Underpinning more intelligent and automated working practices

The demand for data skills reflects the significant shift in the workplace, due to the rise of AI. The enterprise leaders who took part in the study believe employee working practices will change to become more collaborative, with intelligent tools helping them make better decisions (80%) and become more productive (82%).

To realise its potential, 37% of C-level respondents predict their organisation will hire a Chief Automation Officer within the next 3 years, rising to 100% within the next decade. But the investment cannot end at senior hires; those on the front line need support during this transition. And 57% of employees surveyed believe that data literacy will help them stay relevant in their role with the growing use of AI.

“We often hear people talk about how employees need to understand how Artificial Intelligence will change how they complete their role, but more importantly we need to be helping them develop the skills that enable them to add value to the output of these intelligent algorithms,” said Elif Tutuk, VP of Innovation & Design at Qlik. “Data literacy will be critical in extending workplace collaboration beyond human-to-human engagements, to employees augmenting machine intelligence with creativity and critical thinking.”

The true value of data literacy on the talent market

The shift toward a more data-oriented and automated workplace creates a massive opportunity for those with data literacy skills. Every single business leader surveyed reported that they would offer a salary increase for candidates that could demonstrate their data literacy. On average, they would offer a 24% salary increase for demonstrating this skillset. For the average UK employee, this translates into an additional £7.6K to their annual salary.

Despite being perceived as critical to the success of the enterprise – both today and in the future – just 13% of employees surveyed feel fully confident in their data literacy skills. Yet, the most common belief among UK enterprise leaders is that it is an individual’s responsibility, over that of their current employer or educational institutions, to prepare themselves with the skills for the future workplace.

Where organisations are increasing their data literacy training, our research shows that it is primarily offered to those working in specific data related roles (59%), such as data analysts and data scientists. Far fewer organisations offer this training to those working in marketing, HR and finance (10%, 17% and 13% respectively) despite the majority of employees working in these functions stating data literacy is already necessary to fulfil their current role (69%, 56% and 75% respectively).

Over three-quarters (76%) of employees are instead investing their own time and money (58%) to plug the professional skills gap needed for the future enterprise – with these employees spending an average of nearly 7 hours each month and nearly £2.6K each year. Some vote with their feet, with 32% of employees reporting having left a job in the past 12 months due to their employer not offering enough upskilling and training opportunities.

“Over the past few years, investments in digitizing most business processes have transformed the data resources available, and this will continue as we move toward a more intelligent and automated workplace,” said Dr. Paul Barth, Global Head of Data Literacy at Qlik. “But investment in leading-edge data platforms has revealed a large—and expanding—gap in data literacy skills in the workforce. To become a data-driven company, where employees regularly use data and analytics to make better decisions and take informed actions, business leaders need to make investments in upskilling workers in every role to close the data literacy gap.”

The Data Literacy: The Upskilling Evolution report can be downloaded here.

How intelligent technologies are helping marketers predict challenges during the Covid-19 pandemic and beyond
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By Saranya Babu, Senior Vice President of Marketing, Wrike

Marketing is undeniably one of the most important aspects of modern business strategy. Whether it’s developing a unique brand image, or carrying out specific campaigns to attract the right audience, the activities of the marketing department are at the centre of driving growth and revenue within any organisation. 

This year, marketers have been presented with an entirely new and unexpected challenge – how to navigate a global pandemic. The economic uncertainty surrounding this ongoing crisis has forced many businesses to redefine their brand identity, in order to distinguish themselves from their competitors and survive. 

While many businesses are accustomed to crisis management, the scale of this pandemic calls for a more comprehensive approach. In order to truly speak to their audiences during these unprecedented times and beyond, marketers must focus on developing a meaningful and consistent brand image, with each and every project being a success.  

Make no mistakes with integrated insights

With businesses of all shapes and sizes facing a long road to recovery, tough decisions are being made across the board. Unfortunately, many marketing departments are bearing the brunt of industry-wide cut-backs. In fact, dips in business revenue have resulted in the largest ever decline in spending, with over  41% of UK firms  reducing their marketing budgets in the third quarter of 2020 as a direct result of the pandemic.  

During this time of turmoil, instant access to real-time performance metrics within existing work management platforms is essential for marketing teams, especially given the speed at which things are changing. The ability to examine the progress of ongoing projects and campaigns, their strengths and weaknesses, as well as potential areas for improvement can improve the chances of a successful outcome. 

After all, marketing is dependent on the ability to juggle several tasks at once. This is a lot easier said than done when multiple ads, email, and social campaigns are running simultaneously. Operating on outdated information – even by a day or two – can adversely affect the final outcome of a project. Moreover, as the remote work era continues, visibility will become more important than ever before. The lack of face-to-face communication demands accurate performance metrics in order to track and analyse a campaigns’ progression at any given moment.  

Ahead of the game 

Many different things can derail a project. Additional costs, failure to meet deadlines, or unplanned modifications can all have a negative impact and, ultimately, cost a business – especially in our current landscape. In order to increase the likelihood of success for a project and limit any potential risk, marketing teams should look to predict and plan for a series of different possibilities from the offset.  

This is where modern technologies – such as artificial intelligence (AI) and machine learning (ML) – come into play. These technologies can pinpoint at-risk projects and provide an early diagnosis, so that teams can take necessary action to minimise risk and solve any potential challenges before they even occur. By recognising signals and patterns based on hundreds of factors, including past campaign results, work progress, organisation history, and work complexity, the insights provided by these technologies can help to salvage entire projects. 

With intelligent insights readily available, marketing teams can work towards prioritising matters of high-importance, such as mitigating and managing risk. This can be done by evaluating a project’s ‘risk tolerance’. In other words, how much can you allow before you need to act. This is a crucial step in any project management process, enabling marketers to choose the most effective response and ensure that resources are being used in the most effective way.  

As competition rises and budgets shrink, marketing teams are under increasing pressure to deliver. Connecting with desired audiences through brand consistency, strong messaging, and impactful campaigns is still important. However – thanks to the increased pressures brought by the pandemic – there is no longer any room for error. Therefore, guaranteeing all activities are on course and risk is at an all-time-low must be a priority. While there isn’t a single ingredient for success during these unprecedented times, integrated insights and AI and ML technologies could play a significant part in enabling marketing teams to predict and mitigate any possible risks ahead of time. 

Boostify partners Third Foundation on customer experience tech
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Yorkshire-based Boostify has teamed up with machine learning and Artificial Intelligence (AI) start-up Third Foundation to strengthen its customer experience optimisation (CXO) platform.

Specialising in behavioural targeting and advanced content personalisation, Boostify’s solution enables brands to collect in-depth data insights and segment website visitors, allowing them to deploy customised messaging and offers throughout a user’s entire site journey.

Integrating Google Cloud Partner company Third Foundation’s ‘Prime Radiant’ technology enables machine learning to help highlight trends in consumer behaviour that would otherwise be unidentifiable. Additionally, it can reduce the time businesses spend manually building customer segments and minimise human error and decisions driven by predictions.

Boostify’s CEO and founder, Jonathan Thirkill, said: “Joining forces with Third Foundation takes smart and engineered data insight to the next level.

“Using advanced machine learning and AI technologies, Third Foundation will improve the quality of our platform’s targeting features, thus enabling us to make content more relevant to individual website visitors.

“This will empower brands to have a better understanding of their online users’ behaviours quickly. And, by really getting to the heart of what content makes them tick, organisations can yield more conversions in less time.

“We’ve been looking to expand Boostify’s offering with machine learning and AI – this solution ticks all the boxes.”

Third Foundation’s CEO, Michael Ward, added: “This is a truly exciting partnership which brings together two businesses at the forefront of their respective industries.

“By combining Third Foundation’s specialist data engineering and machine learning features with what is probably the most advanced CXO platform on the market, we are creating an exciting proposition that could revolutionise the industry.

“In this new dawn of relevance demanded by consumers, this partnership will allow digital marketing agencies and brands to deliver a more relevant online experience, for more of their customers, more often.”

Retailers urged to embrace digital personalisation
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Retails have been urged to extend personalisation at every digital touchpoint and to every individual using AI, in light of more dire warnings on the state of the High Street.

The British Retail Consortium and KPMG have noted the lowest sales figures since 1995 in May, which in a year plagued with closures and CVAs raises the alarm for further decline in the UK high street in the coming months.

According to Raj Badarinath, VP Ecosystems at RichRelevance, brands and retailers are desperately looking for a solution, but stubbornly ignoring the most critical factor: what customers want.

Badarinath asserts that instead of exploring their customers as individuals (not rough marketing-made segments) they keep holding on to outdated personalisation tactics that are clearly not good enough.

“It is disappointing to see retail sales falling year on year in the UK. It’s a tricky time for UK retailers – as they battle on multiple fronts: monopolies like Amazon, ankle biters such as DVNBs (Digitally Native Vertical Brands) and more,” said Badarinath.

“UK consumers today are short on time and inundated with the problem of choice – too much content, product, offers and more. Retailers should reduce decision fatigue by extending personalization at every digital touchpoint and to every individual using AI, which provides the technical ability to do so for the first time. Retailers realize that the UK consumer is fickle and easily wooed, so techniques like hyper-personalization ensure a seamless, memorable customer experience, to increase repeat sales and improve overall lifetime value.”

Privacy concerns hindering Allo’s chance of messaging success?
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Although reports have suggested that Google’s newly launched messaging service, Allo, is already causing some privacy concerns, the multinational technology company is defiant in ensuring users can safely navigate the app – despite its integration with Google’s new artificial intelligence (AI) assistant, which requires all messages to be sent without end-to-end encryption.

As a result, not only can Google’s Assistant access and read the messages, but Google as a whole can too; as well as national security organisations. With its developers announcing back in May that Allo would include revolutionary message retention policies unheard of among other messaging apps such as iMessage and WhatsApp, industry insiders have found that all messages are linked directly to an account and stored indefinitely – failing to keep its promise of ‘transiently’ storing chat logs and making sure all conversations are not permanently placed on Google’s servers.

A Google spokesperson said in a statement: “We’ve given users transparency and control over their data in Google Allo. And our approach is simple – your chat history is saved for you until you choose to delete it.”

“You can delete single messages or entire conversations in Allo. We also provide the option to chat in Incognito mode, where messages are end-to-end encrypted and you can set a timer to automatically delete messages for your device and the person you’re chatting with’s device at a set time.”

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