Shadowing Practice: Harnessing generative AI in architecture, engineering & construction - Learn English Speaking with Video
Choose a practice mode
Each mode opens a full-screen practice room.
114 sentences
If sentences are too short or too long, click Edit to adjust them.
1
Use cases that certainly a lot of our clients are getting interested and excited about are probably into three or four buckets.
2
So the first of those is everything around design productivity.
3
So the thing that's very cool about Gen AI
4
and in fact AI more broadly is it allows you to start to
5
automate some of the tasks which take engineers
6
and architects a lot of time at the moment
7
but don't necessarily add huge amounts of values
8
that might be you know generating design specifications
9
it might be about deciding exactly how high off the ground the door handle should be right
10
and the great thing about design optimization is it creates capacity with engineers
11
and architects to really focus on the highly complex novel problems right which is which is quite an exciting opportunity.
12
I think the other kind of big collection and use cases we see is everything around planning and scheduling.
13
So, yeah, planning and construction planning is typically a bit of a dark art in construction.
14
There is some science behind it, but it's definitely there's elements of being a dark art,
15
and that's borne out with some of the schedule adherence we see typically in construction and infrastructure projects,
16
with projects typically running over budget and over time.
17
There are tools out there and companies out there
18
that actually use AI to learn from historic project delivery to improve the accuracy of scheduled forecasting
19
and actually do that almost in real time.
20
So day by day
21
or week by week you're coming up with a more accurate view of the schedule
22
and actually recommendations on how you might redeploy resources with a schedule.
23
Some of the most exciting opportunities
24
and most disruptive are looking at the impact of environmental impact on design
25
and feasibility so looking at future scenarios where flooding wind storms excessive heat will impact on a concept
26
so as we help clients and we help design
27
and engineering companies plan ahead and think of their optimal design there are
28
so many different scenarios
29
that we can now generate using AI to really think ahead of the future and make sure that these assets,
30
these important buildings that are getting constructed or road infrastructures are going to stand the test of time.
31
The engineering challenges we have are more complex than what we've ever seen before over the next 30 to 50 years,
32
right, when we talk about the decarbonisation challenge,
33
and we're trying to do that when we've got a capacity constraint in the industry we don't have enough engineers, we don't have enough architects,
34
we don't have enough capacity in the construction industry.
35
Gen AI, AI and actually digital tools more broadly are a way of bridging that productivity gap.
36
Look, this isn't the panacea for all solutions, there are going to be limitations for this
37
and I think what we need to be aware of that this technology is not about replacing people, it's about augmenting the process,
38
about making sure that we're using human interaction on the most complex elements
39
and that the basics are done right first time we get to brilliant basics quickly
40
but there's a lot of buzz and excitement rightly
41
so about gen ai and ai at the moment
42
and some of the use cases we've described it have huge potential massively exciting but it's really important to remember that
43
construction is a it's the biggest industry in the world
44
it's one of the most fragmented it's mainly made up of small
45
and medium you know artisanal craftspeople and small construction companies
46
and it's always going to be a hands -on physical business
47
that relies on skilled hard working people on the front line
48
and that that isn't going to change anytime soon right
49
so I think we need to be need to recognize
50
that AI has an opportunity to you know augment the work
51
that we do on a site it has an opportunity to accelerate design
52
and streamline the design process
53
but it's not going to change the kind of physical act
54
of building stuff out on a out on a building site
55
which the other kind of reality check we need to do is
56
that this depends on data as well and this is something
57
that most industries struggle with that construction particularly struggles with
58
because of this level of fragmentation
59
and you need to have a solid data layer to be
60
able to deliver many of these use cases one of the challenges is
61
that the industry from an engineering perspective is based on hours
62
and suddenly there's a potential to do things instantly in a nanosecond at zero real cost how do we monetize
63
that how do we incentivize
64
the technology companies the engineering companies
65
and the owners to collaborate ultimately an owner will benefit
66
when their schedules reduce their cost to build
67
and time to market is reduced and we're talking about projects
68
that are often in the millions if not billions
69
so how do we help the ecosystem the supply chain ecosystem benefit from
70
that transformation because otherwise there'll be as much of a risk of low
71
and slow adoption as there is of going too fast and getting it wrong.
72
The question
73
that I'm hearing a lot is what does this mean for my business is it kind of exciting hype
74
that I can kind of ignore for a few months
75
or is it something that's fundamentally going to change the business
76
and yeah every business will be different right
77
but the way we think about it is as an engineering
78
company how can you use AI to more accurately predict
79
and monitor energy consumption in an office building in real time and offer real -time solutions to optimise energy consumption.
80
I would be looking and guiding organisations towards finding some low -hanging fruit,
81
something that is contained and managed that you can change as a whole system level.
82
Because this isn't just about adopting technology quickly.
83
It's about changing the sales and marketing teams, the incentives for those sales teams to sell a new solution in a different commercial way.
84
And the potential impact of working new in a new way where it's not an hours -based business
85
or a lump sum type business is quite huge.
86
And I can see some companies getting stuck with the enormity of this.
87
So run the whole changes through the entire lifecycle of the services
88
that are provided to the clients through to commercials and billing
89
and make sure the whole team are working in
90
that way almost as a product team and taking that to market and learning from that is really important.
91
Although the technology is relatively new actually the approach to transformation is one
92
that we've we've seen before we're familiar with right so that
93
and there's two dimensions to it the first is you identify the business domains
94
and the use cases where this is going to create most value right
95
so it might be to improve your win rate
96
and tendering it might be to reduce accidents on site it might be to improve engineering productivity
97
but which use cases are going to create real business value
98
and then on the feasibility right
99
so do we have the data to be able to do this do we have the systems and
100
if not is it going to be a significant investment to
101
get the right systems in place do we have um actual skills to help us build uh
102
and administer the technology and either build or integrate with the right models
103
and then from that develop a list of a short list of use cases
104
and go and execute the pilots before scaling right
105
but it's it's very easy to get excited about the technology for technology's sake
106
but it must be grounded in in in business impact at the end the day.
107
I think AEC companies need to focus on the value pools.
108
Where is this going to have the biggest impact but not go too large at the beginning?
109
Really get something proven and working and deployed and get the rest of the organization behind it.
110
That's how I'd be tackling this but also you know engineers like to design,
111
they like to own and build and there's going to be a preference to own
112
and build this technology and I think that existing technology companies
113
and startups are pure play invested in this area already and have already been moving in this direction.
114
So adopting and working with the right technology partners from the outset is really important.
Download App
Everything you need to speak fluently
AI PronunciationScore every sentence
IPA PracticeMaster every sound
VocabularyBuild your word bank
Vocab GameLearn while playing
📺 Same Channel
C14
Reinventing construction: Seven ways forward
Daily ConversationUniversity StudentsWorking Adults
C11
How does modular construction impact costs?
Daily ConversationUniversity Students
C12
How demand for workforce skills will change with automation: A minute with MGI
Business EnglishUniversity StudentsWorking Adults
✨ Recommend Video
C11
553 sentences
How AI Is Changing Strategy—and 4 Skills Leaders Need Next
Daily ConversationUniversity StudentsWorking Adults
C11
33 sentences
Enhancing AV Simulation with Generative AI - DRIVE Labs Ep. 36
Daily ConversationUniversity StudentsWorking Adults
C17
75 sentences
What AI can (and can't) currently do in a real lab | Jennifer Doudna
Daily ConversationUniversity StudentsWorking Adults
C11
105 sentences
AI Governance Explained: Ethical, Transparent & Accountable AI for the Future
Daily ConversationUniversity StudentsWorking Adults
C11
315 sentences
How Disruptive Will Generative AI Be? A Micro-Level Analysis of Evidence and Expectations
Daily ConversationUniversity StudentsWorking Adults
C13
188 sentences
NVIDIA GTC 2025 - Keynote Highlights by NVIDIA CEO Jensen Huang
Daily ConversationUniversity StudentsWorking Adults
C12
136 sentences
Is ML Engineering Dead? (AI vs ML Engineer)
Daily ConversationUniversity StudentsWorking Adults
C13
26 sentences
How does AI actually work?
Daily ConversationUniversity StudentsWorking Adults
C14
106 sentences
DPM Gan Kim Yong's Speech at the "Trust and AI: Navigating a World in Transition" Leaders Dialogue
Daily ConversationUniversity StudentsWorking Adults
C15
182 sentences
How to Become an AI Product Manager in 2026 | Ex-Google, Microsoft
Daily ConversationUniversity StudentsWorking Adults
C11
74 sentences
AI & Inequality | Daron Acemoglu: Big Tech poses risks as AI reshapes society
Daily ConversationUniversity StudentsWorking Adults
Vocabulary and speaking notes for this lesson
This speaking lesson is built on the video “Harnessing generative AI in architecture, engineering & construction”. The speaker keeps coming back to these words: technology, design, companies, construction, cases. This video has 114 sentences and 1438 words to shadow. The speech runs for 8:41. The speaker talks at a natural 166 words per minute, close to everyday conversation. 87% of the words are among the 3,000 most common in English, so the vocabulary is easy to follow.
Key vocabulary in this video
15 words from the video worth learning, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| productivity noun | /ˌpɹɒdʌkˈtɪvəti/ | The state of being productive, fertile, or efficient. |
| architect noun | /ˈɑɹ.kɪˌtɛkt/ | A professional who designs buildings or other structures, or who prepares plans and superintends construction. |
| element noun | /ˈɛləmənt/ | One of the simplest or essential parts or principles of which anything consists, or upon which the constitution or fundamental powers of anything are based. |
| infrastructure noun | /ˈɪnfɹəˌstɹʌkt͡ʃə/ | An underlying base or foundation for a building, organization, or system. |
| skill noun | /skɪl/ | A capacity to do something well; a technique, an ability, usually acquired or learned, as opposed to abilities that are regarded as innate. |
| consumption noun | /kənˈsʌmp.ʃən/ | The act of eating, drinking or using. |
| generate verb | /ˈd͡ʒɛn.ə.ɹeɪt/ | To bring into being; give rise to. |
| transformation noun | /ˌtɹæns.fɔɹˈmeɪ.ʃən/ | The act of transforming or the state of being transformed. |
| adopt verb | /əˈdɑpt/ | To take voluntarily (a child of other parents) to be in the place of, or as, one's own child. |
| scenario noun | /sɪˈnɛəɹioʊ/ | An outline or model of an expected or supposed sequence of events. |
| broadly adverb | /ˈbɹɔːdli/ | Widely and openly. |
| ecosystem noun | /ˈikoʊˌsɪstəm/ | A system formed by an ecological community and its environment that functions as a unit. |
| ignore verb | /ɪɡˈnɔː/ | To deliberately not listen or pay attention to. |
| necessarily adverb | /ˌnɛs.əˈsɛɹ.ə.li/ | Inevitably; of necessity. |
| layer noun | /ˈleɪ̯ɚ/ | A single thickness of some material covering a surface. |
Phrasal verbs you will hear
| Word | Meaning |
|---|---|
| come up with verb | To manage to produce, deliver, or present (something) by inventing, creating, thinking of, or obtaining it. |
| plan ahead verb | To schedule or plan extensively for problems before it is needed; to come up with solutions before problems occur; to prepare for future situations. |
| run over verb | To exceed the allotted time. |
Grammar in this video
The structures the speaker uses most, with the exact words from the video:
| Structure | In the video |
|---|---|
| Passive voice be + past participle — the focus is on what happens, not who does it | are done · is based · is reduced |
| Present perfect have/has + past participle — a past action that still matters now | we've ever seen · we've described · we've seen |
Pronunciation to watch
The speaker uses 20 contractions and reduced forms, such as we've, don't, we're. Say them the short way, as you hear them.
- The “sh” and “zh” sounds: consumption /kənˈsʌmp.ʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, organisation /ˈɔː.ɡə.naɪˌzeɪ.ʃən/, interaction /ˌɪn.təˈɹæk.ʃən/, adoption /əˈdɑp.ʃən/
- Long words — get the stress right: productivity /ˌpɹɒdʌkˈtɪvəti/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, ecosystem /ˈikoʊˌsɪstəm/, necessarily /ˌnɛs.əˈsɛɹ.ə.li/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
- Record yourself and compare with the original, paying attention to words like productivity, architect, element.
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.